Overview of the JET results in support to ITER

PAPER • OPEN ACCESS Overview of the JET results in support to ITER To cite this article: X. Litaudon et al 2017 Nucl. Fusion 57 102001 View the article online for updates and enhancements. Related content Chapter 4: Power and particle control A. Loarte, B. Lipschultz, A.S. Kukushkin et al. - Overview of the JET results F. Romanelli and on behalf of JET Contributors - Chapter 2: Plasma confinement and transport E.J. Doyle (Chair Transport Physics), W.A. Houlberg (Chair Confinement Database and Modelling), Y. Kamada (Chair Pedestal and Edge) et al. - Recent citations Beryllium, tungsten and their alloys Be 2 W and Be 12 W: Surface defect energetics from density functional theory calculations L. Chen et al - Lifshitz calculations of Hamaker constants for fusion relevant materials P. Tolias - A new perspective on MHD mode identification of IR-T1 tokamak plasma by frequency filtering and fitting method M.R. Ghanbari et al - This content was downloaded from IP address 150.214.182.32 on 12/07/2018 at 12:39 1 © 2017 Euratom Printed in the UK Nuclear Fusion Overview of the JET results in support to ITER X.Litaudon35, S.Abduallev39, M.Abhangi46, P.Abreu53, M.Afzal7, K.M.Aggarwal29, T.Ahlgren101, J.H.Ahn8, L.Aho-Mantila112, N.Aiba69, M.Airila112, R.Albanese105, V.Aldred7, D.Alegre93, E.Alessi45, P.Aleynikov55, A.Alfier12, A.Alkseev72, M.Allinson7, B.Alper7, E.Alves53, G.Ambrosino105, R.Ambrosino106, L.Amicucci90, V.Amosov88, E.Andersson Sundén22, M.Angelone90, M.Anghel85, C.Angioni62, L.Appel7, C.Appelbee7, P.Arena30, M.Ariola106, H.Arnichand8, S.Arshad41, A. Ash7, N. Ashikawa68, V.Aslanyan64, O.Asunta1, F.Auriemma12, Y.Austin7, L.Avotina103, M.D.Axton7, C.Ayres7, M.Bacharis24, A.Baciero57, D.Baião53, S.Bailey7, A.Baker7, I.Balboa7, M.Balden62, N.Balshaw7, R.Bament7, J.W.Banks7, Y.F.Baranov7, M.A.Barnard7, D.Barnes7, M.Barnes27, R.Barnsley55, A.Baron Wiechec7, L.Barrera Orte34, M.Baruzzo12, V.Basiuk8, M.Bassan55, R.Bastow7, A.Batista53, P.Batistoni90, R.Baughan7, B.Bauvir55, L.Baylor73, B.Bazylev56, J.Beal110, P.S.Beaumont7, M.Beckers39, B.Beckett7, A.Becoulet8, N.Bekris35, M.Beldishevski7, K.Bell7, F.Belli90, M.Bellinger7, É.Belonohy62, N.Ben Ayed7, N.A.Benterman7, H.Bergsåker42, J.Bernardo53, M.Bernert62, M.Berry7, L.Bertalot55, C.Besliu7, M.Beurskens63, B.Bieg61, J.Bielecki47, T.Biewer73, M.Bigi12, P.Bílková50, F.Binda22, A.Bisoffi31, J.P.S.Bizarro53, C.Björkas101, J.Blackburn7, K.Blackman7, T.R.Blackman7, P.Blanchard33, P.Blatchford7, V.Bobkov62, A.Boboc7, G.Bodnár113, O.Bogar18, I.Bolshakova60, T.Bolzonella12, N.Bonanomi97, F.Bonelli56, J.Boom62, J.Booth7, D.Borba35,53, D.Borodin39, I.Borodkina39, A.Botrugno90, C.Bottereau8, P.Boulting7, C.Bourdelle8, M.Bowden7, C.Bower7, C.Bowman110, T.Boyce7, C.Boyd7, H.J.Boyer7, J.M.A.Bradshaw7, V.Braic87, R.Bravanec40, B.Breizman107, S.Bremond8, P.D.Brennan7, S.Breton8, A.Brett7, S.Brezinsek39, M.D.J.Bright7, M.Brix7, W.Broeckx78, M.Brombin12, A.Brosławski65, D.P.D.Brown7, M.Brown7, E.Bruno55, J.Bucalossi8, J.Buch46, J.Buchanan7, M.A.Buckley7, R.Budny76, H.Bufferand8, M.Bulman7, N.Bulmer7, P.Bunting7, P.Buratti90, A.Burckhart62, A.Buscarino30, A.Busse7, N.K.Butler7, I.Bykov42, J.Byrne7, P.Cahyna50, G.Calabrò90, I.Calvo57, Y.Camenen4, P.Camp7, D.C.Campling7, J.Cane7, B.Cannas17, A.J.Capel7, P.J.Card7, A.Cardinali90, P.Carman7, M.Carr7, D.Carralero62, L.Carraro12, B.B.Carvalho53, I.Carvalho53, P.Carvalho53, F.J.Casson7, C.Castaldo90, N.Catarino53, J.Caumont7, F.Causa90, R.Cavazzana12, K.Cave-Ayland7, M.Cavinato12, M.Cecconello22, S.Ceccuzzi90, E.Cecil76, A.Cenedese12, R.Cesario90, C.D.Challis7, M.Chandler7, D.Chandra46, C.S.Chang76, A.Chankin62, I.T.Chapman7, S.C.Chapman28, M.Chernyshova49, G.Chitarin12, G.Ciraolo8, D.Ciric7, J.Citrin38, F.Clairet8, E.Clark7, M.Clark7, R.Clarkson7, D.Clatworthy7, C.Clements7, M.Cleverly7, X. Litaudon etal Printed in the UK 102001 NUFUAU © 2017 Euratom 57 Nucl. Fusion NF 10.1088/1741-4326/aa5e28 Paper 10 Nuclear Fusion IOP Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. International Atomic Energy Agency 2017 1741-4326 1741-4326/17/102001+41$33.00 https://doi.org/10.1088/1741-4326/aa5e28 Nucl. Fusion 57 (2017) 102001 (41pp) X. Litaudon etal 2 J.P.Coad7, P.A.Coates7, A.Cobalt7, V.Coccorese105, V.Cocilovo90, S.Coda33, R.Coelho53, J.W.Coenen39, I.Coffey29, L.Colas8, S.Collins7, D.Conka103, S.Conroy22, N.Conway7, D.Coombs7, D.Cooper7, S.R.Cooper7, C.Corradino30, Y.Corre8, G.Corrigan7, S.Cortes53, D.Coster62, A.S.Couchman7, M.P.Cox7, T.Craciunescu86, S.Cramp7, R.Craven7, F.Crisanti90, G.Croci97, D.Croft7, K.Crombé15, R.Crowe7, N.Cruz53, G.Cseh113, A.Cufar81, A.Cullen7, M.Curuia85, A.Czarnecka49, H.Dabirikhah7, P.Dalgliesh7, S.Dalley7, J.Dankowski47, D.Darrow76, O.Davies7, W.Davis55,76, C.Day56, I.E.Day7, M.De Bock55, A.de Castro57, E.de la Cal57, E.de la Luna57, G.De Masi12, J.L.de Pablos57, G.De Temmerman55, G.De Tommasi105, P.de Vries55, K.Deakin7, J.Deane7, F.Degli Agostini12, R.Dejarnac50, E.Delabie73, N.den Harder38, R.O.Dendy7, J.Denis8, P.Denner39, S.Devaux62,104, P.Devynck8, F.Di Maio55, A.Di Siena62, C.Di Troia90, P.Dinca86, R.D’Inca62, B.Ding51, T.Dittmar39, H.Doerk62, R.P.Doerner9, T.Donné34, S.E.Dorling7, S.Dormido-Canto93, S.Doswon7, D.Douai8, P.T.Doyle7, A.Drenik62,81, P.Drewelow63, P.Drews39, Ph.Duckworth55, R.Dumont8, P.Dumortier58, D.Dunai113, M.Dunne62, I.Ďuran50, F.Durodié58, P.Dutta46, B.P.Duval33, R.Dux62, K.Dylst78, N.Dzysiuk22, P.V.Edappala46, J.Edmond7, A.M.Edwards7, J.Edwards7, Th.Eich62, A.Ekedahl8, R.El-Jorf7, C.G.Elsmore7, M.Enachescu84, G.Ericsson22, F.Eriksson16, J.Eriksson22, L.G.Eriksson36, B.Esposito90, S.Esquembri94, H.G.Esser39, D.Esteve8, B.Evans7, G.E.Evans7, G.Evison7, G.D.Ewart7, D.Fagan7, M.Faitsch62, D.Falie86, A.Fanni17, A.Fasoli33, J.M.Faustin33, N.Fawlk7, L.Fazendeiro53, N.Fedorczak8, R.C.Felton7, K.Fenton7, A.Fernades53, H.Fernandes53, J.Ferreira53, J.A.Fessey7, O.Février8, O.Ficker50, A.Field7, S.Fietz62, A.Figueiredo53, J.Figueiredo53,35, A.Fil8, P.Finburg7, M.Firdaouss8, U.Fischer56, L.Fittill7, M.Fitzgerald7, D.Flammini90, J.Flanagan7, C.Fleming7, K.Flinders7, N.Fonnesu90, J.M.Fontdecaba57, A.Formisano79, L.Forsythe7, L.Fortuna30, E.Fortuna-Zalesna19, M.Fortune7, S.Foster7, T.Franke34, T.Franklin7, M.Frasca30, L.Frassinetti42, M.Freisinger39, R.Fresa98, D.Frigione90, V.Fuchs50, D.Fuller35, S.Futatani6, J.Fyvie7, K.Gál34,62, D.Galassi2, K.Gałązka49, J.Galdon-Quiroga92, J.Gallagher7, D.Gallart6, R.Galvão10, X.Gao51, Y.Gao39, J.Garcia8, A.Garcia-Carrasco42, M.García-Muñoz92, J.-L.Gardarein3, L.Garzotti7, P.Gaudio95, E.Gauthier8, D.F.Gear7, S.J.Gee7, B.Geiger62, M.Gelfusa95, S.Gerasimov7, G.Gervasini45, M.Gethins7, Z.Ghani7, M.Ghate46, M.Gherendi86, J.C.Giacalone8, L.Giacomelli45, C.S.Gibson7, T.Giegerich56, C.Gil8, L.Gil53, S.Gilligan7, D.Gin54, E.Giovannozzi90, J.B.Girardo8, C.Giroud7, G.Giruzzi8, S.Glöggler62, J.Godwin7, J.Goff7, P.Gohil43, V.Goloborod’ko102, R.Gomes53, B.Gonçalves53, M.Goniche8, M.Goodliffe7, A.Goodyear7, G.Gorini97, M.Gosk65, R.Goulding76, A.Goussarov78, R.Gowland7, B.Graham7, M.E.Graham7, J.P.Graves33, N.Grazier7, P.Grazier7, N.R.Green7, H.Greuner62, B.Grierson76, F.S.Griph7, C.Grisolia8, D.Grist7, M.Groth1, R.Grove73, C.N.Grundy7, J.Grzonka19, D.Guard7, C.Guérard34, C.Guillemaut8,53, R.Guirlet8, C.Gurl7, H.H.Utoh69, L.J.Hackett7, S.Hacquin8,35, A.Hagar7, R.Hager76, A.Hakola112, M.Halitovs103, S.J.Hall7, S.P.Hallworth Cook7, C.Hamlyn-Harris7, K.Hammond7, C.Harrington7, J.Harrison7, D.Harting7, F.Hasenbeck39, Y.Hatano108, D.R.Hatch107, T.D.V.Haupt7, J.Hawes7, N.C.Hawkes7, J.Hawkins7, P.Hawkins7, P.W.Haydon7, N.Hayter7, S.Hazel7, P.J.L.Heesterman7, K.Heinola101, Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 3 C.Hellesen22, T.Hellsten42, W.Helou8, O.N.Hemming7, T.C.Hender7, M.Henderson55, S.S.Henderson21, R.Henriques53, D.Hepple7, G.Hermon7, P.Hertout8, C.Hidalgo57, E.G.Highcock27, M.Hill7, J.Hillairet8, J.Hillesheim7, D.Hillis73, K.Hizanidis70, A.Hjalmarsson22, J.Hobirk62, E.Hodille8, C.H.A.Hogben7, G.M.D.Hogeweij38, A.Hollingsworth7, S.Hollis7, D.A.Homfray7, J.Horáček50, G.Hornung15, A.R.Horton7, L.D.Horton36, L.Horvath110, S.P.Hotchin7, M.R.Hough7, P.J.Howarth7, A.Hubbard64, A.Huber39, V.Huber39, T.M.Huddleston7, M.Hughes7, G.T.A.Huijsmans55, C.L.Hunter7, P.Huynh8, A.M.Hynes7, D.Iglesias7, N.Imazawa69, F.Imbeaux8, M.Imríšek50, M.Incelli109, P.Innocente12, M.Irishkin8, I.Ivanova-Stanik49, S.Jachmich58,35, A.S.Jacobsen83, P.Jacquet7, J.Jansons103, A.Jardin8, A.Järvinen1, F.Jaulmes38, S.Jednoróg49, I.Jenkins7, C.Jeong20, I.Jepu86, E.Joffrin8, R.Johnson7, T.Johnson42, JaneJohnston7, L.Joita7, G.Jones7, T.T.C.Jones7, K.K.Hoshino69, A.Kallenbach62, K.Kamiya69, J.Kaniewski7, A.Kantor7, A.Kappatou62, J.Karhunen1, D.Karkinsky7, I.Karnowska7, M.Kaufman73, G.Kaveney7, Y.Kazakov58, V.Kazantzidis70, D.L.Keeling7, T.Keenan7, J.Keep7, M.Kempenaars7, C.Kennedy7, D.Kenny7, J.Kent7, O.N.Kent7, E.Khilkevich54, H.T.Kim35, H.S.Kim80, A.Kinch7, C.king7, D.King7, R.F.King7, D.J.Kinna7, V.Kiptily7, A.Kirk7, K.Kirov7, A.Kirschner39, G.Kizane103, C.Klepper73, A.Klix56, P.Knight7, S.J.Knipe7, S.Knott96, T.Kobuchi69, F.Köchl111, G.Kocsis113, I.Kodeli81, L.Kogan7, D.Kogut8, S.Koivuranta112, Y.Kominis70, M.Köppen39, B.Kos81, T.Koskela1, H.R.Koslowski39, M.Koubiti4, M.Kovari7, E.Kowalska-Strzęciwilk49, A.Krasilnikov88, V.Krasilnikov88, N.Krawczyk49, M.Kresina8, K.Krieger62, A.Krivska58, U.Kruezi7, I.Książek48, A.Kukushkin72, A.Kundu46, T.Kurki-Suonio1, S.Kwak20, R.Kwiatkowski65, O.J.Kwon13, L.Laguardia45, A.Lahtinen101, A.Laing7, N.Lam7, H.T.Lambertz39, C.Lane7, P.T.Lang62, S.Lanthaler33, J.Lapins103, A.Lasa101, J.R.Last7, E.Łaszyńska49, R.Lawless7, A.Lawson7, K.D.Lawson7, A.Lazaros70, E.Lazzaro45, J.Leddy110, S.Lee66, X.Lefebvre7, H.J.Leggate32, J.Lehmann7, M.Lehnen55, D.Leichtle41, P.Leichuer7, F.Leipold55,83, I.Lengar81, M.Lennholm36, E.Lerche58, A.Lescinskis103, S.Lesnoj7, E.Letellier7, M.Leyland110, W.Leysen78, L.Li39, Y.Liang39, J.Likonen112, J.Linke39, Ch.Linsmeier39, B.Lipschultz110, G.Liu55, Y.Liu51, V.P.Lo Schiavo105, T.Loarer8, A.Loarte55, R.C.Lobel7, B.Lomanowski1, P.J.Lomas7, J.Lönnroth1,35, J.M.López94, J.López-Razola57, R.Lorenzini12, U.Losada57, J.J.Lovell7, A.B.Loving7, C.Lowry36, T.Luce43, R.M.A.Lucock7, A.Lukin74, C.Luna5, M.Lungaroni95, C.P.Lungu86, M.Lungu86, A.Lunniss110, I.Lupelli7, A.Lyssoivan58, N.Macdonald7, P.Macheta7, K.Maczewa7, B.Magesh46, P.Maget8, C.Maggi7, H.Maier62, J.Mailloux7, T.Makkonen1, R.Makwana46, A.Malaquias53, A.Malizia95, P.Manas4, A.Manning7, M.E.Manso53, P.Mantica45, M.Mantsinen6, A.Manzanares91, Ph.Maquet55, Y.Marandet4, N.Marcenko88, C.Marchetto45, O.Marchuk39, M.Marinelli95, M.Marinucci90, T.Markovič50, D.Marocco90, L.Marot26, C.A.Marren7, R.Marshal7, A.Martin7, Y.Martin33, A.Martín de Aguilera57, F.J.Martínez93, J.R.Martín-Solís14, Y.Martynova39, S.Maruyama55, A.Masiello12, M.Maslov7, S.Matejcik18, M.Mattei79, G.F.Matthews7, F.Maviglia11, M.Mayer62, M.L.Mayoral34, T.May-Smith7, D.Mazon8, C.Mazzotta90, R.McAdams7, P.J.McCarthy96, K.G.McClements7, O.McCormack12, P.A.McCullen7, D.McDonald34, S.McIntosh7, R.McKean7, J.McKehon7, R.C.Meadows7, A.Meakins7, Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 4 F.Medina57, M.Medland7, S.Medley7, S.Meigh7, A.G.Meigs7, G.Meisl62, S.Meitner73, L.Meneses53, S.Menmuir7,42, K.Mergia71, I.R.Merrigan7, Ph.Mertens39, S.Meshchaninov88, A.Messiaen58, H.Meyer7, S.Mianowski65, R.Michling55, D.Middleton-Gear7, J.Miettunen1, F.Militello7, E.Militello-Asp7, G.Miloshevsky77, F.Mink62, S.Minucci105, Y.Miyoshi69, J.Mlynář50, D.Molina8, I.Monakhov7, M.Moneti109, R.Mooney7, S.Moradi37, S.Mordijck43, L.Moreira7, R.Moreno57, F.Moro90, A.W.Morris7, J.Morris7, L.Moser26, S.Mosher73, D.Moulton7,1, A.Murari12,35, A.Muraro45, S.Murphy7, N.N.Asakura69, Y.S.Na80, F.Nabais53, R.Naish7, T.Nakano69, E.Nardon8, V.Naulin83, M.F.F.Nave53, I.Nedzelski53, G.Nemtsev88, F.Nespoli33, A.Neto41, R.Neu62, V.S.Neverov72, M.Newman7, K.J.Nicholls7, T.Nicolas33, A.H.Nielsen83, P.Nielsen12, E.Nilsson8, D.Nishijima99, C.Noble7, M.Nocente97, D.Nodwell7, K.Nordlund101, H.Nordman16, R.Nouailletas8, I.Nunes53, M.Oberkofler62, T.Odupitan7, M.T.Ogawa69, T.O’Gorman7, M.Okabayashi76, R.Olney7, O.Omolayo7, M.O’Mullane21, J.Ongena58, F.Orsitto11, J.Orszagh18, B.I.Oswuigwe7, R.Otin7, A.Owen7, R.Paccagnella12, N.Pace7, D.Pacella90, L.W.Packer7, A.Page7, E.Pajuste103, S.Palazzo30, S.Pamela7, S.Panja46, P.Papp18, R.Paprok50, V.Parail7, M.Park66, F.Parra Diaz27, M.Parsons73, R.Pasqualotto12, A.Patel7, S.Pathak46, D.Paton7, H.Patten33, A.Pau17, E.Pawelec48, C.Paz Soldan43, A.Peackoc36, I.J.Pearson7, S.-P.Pehkonen112, E.Peluso95, C.Penot55, A.Pereira57, R.Pereira53, P.P.Pereira Puglia7, C.Perez von Thun35,39, S.Peruzzo12, S.Peschanyi56, M.Peterka50, P.Petersson42, G.Petravich113, A.Petre84, N.Petrella7, V.Petržilka50, Y.Peysson8, D.Pfefferlé33, V.Philipps39, M.Pillon90, G.Pintsuk39, P.Piovesan12, A.Pires dos Reis52, L.Piron7, A.Pironti105, F.Pisano17, R.Pitts55, F.Pizzo79, V.Plyusnin53, N.Pomaro12, O.G.Pompilian86, P.J.Pool7, S.Popovichev7, M.T.Porfiri90, C.Porosnicu86, M.Porton7, G.Possnert22, S.Potzel62, T.Powell7, J.Pozzi7, V.Prajapati46, R.Prakash46, G.Prestopino95, D.Price7, M.Price7, R.Price7, P.Prior7, R.Proudfoot7, G.Pucella90, P.Puglia52, M.E.Puiatti12, D.Pulley7, K.Purahoo7, Th.Pütterich62, E.Rachlew25, M.Rack39, R.Ragona58, M.S.J.Rainford7, A.Rakha6, G.Ramogida90, S.Ranjan46, C.J.Rapson62, J.J.Rasmussen83, K.Rathod46, G.Rattá57, S.Ratynskaia82, G.Ravera90, C.Rayner7, M.Rebai97, D.Reece7, A.Reed7, D.Réfy113, B.Regan7, J.Regaña34, M.Reich62, N.Reid7, F.Reimold39, M.Reinhart34, M.Reinke110,73, D.Reiser39, D.Rendell7, C.Reux8, S.D.A.Reyes Cortes53, S.Reynolds7, V.Riccardo7, N.Richardson7, K.Riddle7, D.Rigamonti97, F.G.Rimini7, J.Risner73, M.Riva90, C.Roach7, R.J.Robins7, S.A.Robinson7, T.Robinson7, D.W.Robson7, R.Roccella55, R.Rodionov88, P.Rodrigues53, J.Rodriguez7, V.Rohde62, F.Romanelli90, M.Romanelli7, S.Romanelli7, J.Romazanov39, S.Rowe7, M.Rubel42, G.Rubinacci105, G.Rubino12, L.Ruchko52, M.Ruiz94, C.Ruset86, J.Rzadkiewicz65, S.Saarelma7, R.Sabot8, E.Safi101, P.Sagar7, G.Saibene41, F.Saint-Laurent8, M.Salewski83, A.Salmi112, R.Salmon7, F.Salzedas53, D.Samaddar7, U.Samm39, D.Sandiford7, P.Santa46, M.I.K.Santala1, B.Santos53, A.Santucci90, F.Sartori41, R.Sartori41, O.Sauter33, R.Scannell7, T.Schlummer39, K.Schmid62, V.Schmidt12, S.Schmuck7, M.Schneider8, K.Schöpf102, D.Schwörer32, S.D.Scott76, G.Sergienko39, M.Sertoli62, A.Shabbir15, S.E.Sharapov7, A.Shaw7, R.Shaw7, H.Sheikh7, A.Shepherd7, A.Shevelev54, A.Shumack38, G.Sias17, M.Sibbald7, Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 5 B.Sieglin62, S.Silburn7, A.Silva53, C.Silva53, P.A.Simmons7, J.Simpson7, J.Simpson-Hutchinson7, A.Sinha46, S.K.Sipilä1, A.C.C.Sips36, P.Sirén112, A.Sirinelli55, H.Sjöstrand22, M.Skiba22, R.Skilton7, K.Slabkowska49, B.Slade7, N.Smith7, P.G.Smith7, R.Smith7, T.J.Smith7, M.Smithies110, L.Snoj81, S.Soare85, E.R.Solano35,57, A.Somers32, C.Sommariva8, P.Sonato12, A.Sopplesa12, J.Sousa53, C.Sozzi45, S.Spagnolo12, T.Spelzini7, F.Spineanu86, G.Stables7, I.Stamatelatos71, M.F.Stamp7, P.Staniec7, G.Stankūnas59, C.Stan-Sion84, M.J.Stead7, E.Stefanikova42, I.Stepanov58, A.V.Stephen7, M.Stephen46, A.Stevens7, B.D.Stevens7, J.Strachan76, P.Strand16, H.R.Strauss44, P.Ström42, G.Stubbs7, W.Studholme7, F.Subba75, H.P.Summers21, J.Svensson63, Ł.Świderski65, T.Szabolics113, M.Szawlowski49, G.Szepesi7, T.T.Suzuki69, B.Tál113, T.Tala112, A.R.Talbot7, S.Talebzadeh95, C.Taliercio12, P.Tamain8, C.Tame7, W.Tang76, M.Tardocchi45, L.Taroni12, D.Taylor7, K.A.Taylor7, D.Tegnered16, G.Telesca15, N.Teplova54, D.Terranova12, D.Testa33, E.Tholerus42, J.Thomas7, J.D.Thomas7, P.Thomas55, A.Thompson7, C.-A.Thompson7, V.K.Thompson7, L.Thorne7, A.Thornton7, A.S.Thrysøe83, P.A.Tigwell7, N.Tipton7, I.Tiseanu86, H.Tojo69, M.Tokitani67, P.Tolias82, M.Tomeš50, P.Tonner7, M.Towndrow7, P.Trimble7, M.Tripsky58, M.Tsalas38, P.Tsavalas71, D.Tskhakaya jun102, I.Turner7, M.M.Turner32, M.Turnyanskiy34, G.Tvalashvili7, S.G.J.Tyrrell7, A.Uccello45, Z.Ul-Abidin7, J.Uljanovs1, D.Ulyatt7, H.Urano69, I.Uytdenhouwen78, A.P.Vadgama7, D.Valcarcel7, M.Valentinuzzi8, M.Valisa12, P.Vallejos Olivares42, M.Valovic7, M.Van De Mortel7, D.Van Eester58, W.Van Renterghem78, G.J.van Rooij38, J.Varje1, S.Varoutis56, S.Vartanian8, K.Vasava46, T.Vasilopoulou71, J.Vega57, G.Verdoolaege58, R.Verhoeven7, C.Verona95, G.Verona Rinati95, E.Veshchev55, N.Vianello45, J.Vicente53, E.Viezzer62,92, S.Villari90, F.Villone100, P.Vincenzi12, I.Vinyar74, B.Viola90, A.Vitins103, Z.Vizvary7, M.Vlad86, I.Voitsekhovitch34, P.Vondráček50, N.Vora7, T.Vu8, W.W.Pires de Sa52, B.Wakeling7, C.W.F.Waldon7, N.Walkden7, M.Walker7, R.Walker7, M.Walsh55, E.Wang39, N.Wang39, S.Warder7, R.J.Warren7, J.Waterhouse7, N.W.Watkins28, C.Watts55, T.Wauters58, A.Weckmann42, J.Weiland23, H.Weisen33, M.Weiszflog22, C.Wellstood7, A.T.West7, M.R.Wheatley7, S.Whetham7, A.M.Whitehead7, B.D.Whitehead7, A.M.Widdowson7, S.Wiesen39, J.Wilkinson7, J.Williams7, M.Williams7, A.R.Wilson7, D.J.Wilson7, H.R.Wilson110, J.Wilson7, M.Wischmeier62, G.Withenshaw7, A.Withycombe7, D.M.Witts7, D.Wood7, R.Wood7, C.Woodley7, S.Wray7, J.Wright7, J.C.Wright64, J.Wu89, S.Wukitch64, A.Wynn110, T.Xu7, D.Yadikin16, W.Yanling39, L.Yao89, V.Yavorskij102, M.G.Yoo80, C.Young7, D.Young7, I.D.Young7, R.Young7, J.Zacks7, R.Zagorski49, F.S.Zaitsev18, R.Zanino75, A.Zarins103, K.D.Zastrow7, M.Zerbini90, W.Zhang62, Y.Zhou42, E.Zilli12, V.Zoita86, S.Zoletnik113, I.Zychor65 and JET Contributorsa EUROfusion Consortium JET, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom 1 Aalto University, PO Box 14100, FIN-00076 Aalto, Finland 2 Aix Marseille Université, CNRS, Centrale Marseille, M2P2 UMR 7340, 13451, Marseille, France 3 Aix-Marseille Université, CNRS, IUSTI UMR 7343, 13013 Marseille, France 4 Aix-Marseille Université, CNRS, PIIM, UMR 7345, 13013 Marseille, France 5 Arizona State University, Tempe, AZ, United States of America 6 Barcelona Supercomputing Center, Barcelona, Spain 7 CCFE, Culham Science Centre, Abingdon, Oxon, OX14 3DB, United Kingdom 8 CEA, IRFM, F-13108 Saint Paul Lez Durance, France a We refer to the author list of the paper as JET Contributors. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 6 9 Center for Energy Research, University of California at San Diego, La Jolla, CA 92093, United States of America 10 Centro Brasileiro de Pesquisas Fisicas, Rua Xavier Sigaud, 160, Rio de Janeiro CEP 22290-180, Brazil 11 Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 12 Consorzio RFX, corso Stati Uniti 4, 35127 Padova, Italy 13 Daegu University, Jillyang, Gyeongsan, Gyeongbuk 712-174, Republic of Korea 14 Departamento de Física, Universidad Carlos III de Madrid, 28911 Leganés, Madrid, Spain 15 Department of Applied Physics UG (Ghent University) St-Pietersnieuwstraat 41 B-9000 Ghent, Belgium 16 Department of Earth and Space Sciences, Chalmers University of Technology, SE-41296 Gothenburg, Sweden 17 Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi 09123 Cagliari, Italy 18 Department of Experimental Physics, Faculty of Mathematics, Physics and Informatics Comenius University Mlynska dolina F2, 84248 Bratislava, Slovakia 19 Department of Materials Science, Warsaw University of Technology, PL-01-152 Warsaw, Poland 20 Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Korea 21 Department of Physics and Applied Physics, University of Strathclyde, Glasgow, G4 ONG, United Kingdom 22 Department of Physics and Astronomy, Uppsala University, SE-75120 Uppsala, Sweden 23 Department of Physics, Chalmers University of Technology, SE-41296 Gothenburg, Sweden 24 Department of Physics, Imperial College London, London, SW7 2AZ, United Kingdom 25 Department of Physics, SCI, KTH, SE-10691 Stockholm, Sweden 26 Department of Physics, University of Basel, Basel, Switzerland 27 Department of Physics, University of Oxford, Oxford, OX1 2JD, United Kingdom 28 Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom 29 Department of Pure and Applied Physics, Queens University, Belfast, BT7 1NN, United Kingdom 30 Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Università degli Studi di Catania, 95125 Catania, Italy 31 Dipartimento di Ingegneria Industriale, University of Trento, Trento, Italy 32 Dublin City University (DCU), Dublin, Ireland 33 Ecole Polytechnique Fédérale de Lausanne (EPFL), Swiss Plasma Center (SPC), CH-1015 Lausanne, Switzerland 34 EUROfusion Programme Management Unit, Boltzmannstr. 2, 85748 Garching, Germany 35 EUROfusion Programme Management Unit, Culham Science Centre, Culham, OX14 3DB, United Kingdom 36 European Commission, B-1049 Brussels, Belgium 37 Fluid and Plasma Dynamics, ULB—Campus Plaine—CP 231 Boulevard du Triomphe, 1050 Bruxelles, Belgium 38 FOM Institute DIFFER, Eindhoven, Netherlands 39 Forschungszentrum Jülich GmbH, Institut für Energie- und Klimaforschung—Plasmaphysik, 52425 Jülich, Germany 40 Fourth State Research, 503 Lockhart Dr, Austin, TX, United States of America 41 Fusion for Energy Joint Undertaking, Josep Pl. 2, Torres Diagonal Litoral B3, 08019, Barcelona, Spain 42 Fusion Plasma Physics, EES, KTH, SE-10044 Stockholm, Sweden 43 General Atomics, PO Box 85608, San Diego, CA 92186-5608, United States of America 44 HRS Fusion, West Orange, NJ, United States of America 45 IFP-CNR, via R. Cozzi 53, 20125 Milano, Italy 46 Institute for Plasma Research, Bhat, Gandhinagar-382 428, Gujarat State, India 47 Institute of Nuclear Physics, Radzikowskiego 152, 31-342 Kraków, Poland 48 Institute of Physics, Opole University, Oleska 48, 45-052 Opole, Poland 49 Institute of Plasma Physics and Laser Microfusion, Hery 23, 01-497 Warsaw, Poland 50 Institute of Plasma Physics AS CR, Za Slovankou 1782/3, 182 00 Praha 8, Czechia 51 Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, People’s Republic of China 52 Instituto de Física, Universidade de São Paulo, Rua do Matão Travessa R Nr.187 CEP 05508-090 Cidade Universitária, São Paulo, Brasil 53 Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal 54 Ioffe Physico-Technical Institute, 26 Politekhnicheskaya, St Petersburg 194021, Russian Federation 55 ITER Organization, Route de Vinon, CS 90 046, 13067 Saint Paul Lez Durance, France 56 Karlsruhe Institute of Technology, PO Box 3640, D-76021 Karlsruhe, Germany 57 Laboratorio Nacional de Fusión, CIEMAT, Madrid, Spain 58 Laboratory for Plasma Physics Koninklijke Militaire School—Ecole Royale Militaire, Renaissancelaan 30 Avenue de la Renaissance B-1000, Brussels, Belgium 59 Lithuanian energy institute, Breslaujos g. 3, LT-44403, Kaunas, Lithuania Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 7 60 Magnetic Sensor Laboratory, Lviv Polytechnic National University, Lviv, Ukraine 61 Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, Poland 62 Max-Planck-Institut für Plasmaphysik, D-85748 Garching, Germany 63 Max-Planck-Institut für Plasmaphysik, Teilinsitut Greifswald, D-17491 Greifswald, Germany 64 MIT Plasma Science and Fusion Centre, Cambridge, MA 02139, United States of America 65 National Centre for Nuclear Research (NCBJ), 05-400 Otwock-Świerk, Poland 66 National Fusion Research Institute (NFRI), 169-148 Gwahak-ro, Yuseong-gu, Daejeon 305-806, Republic of Korea 67 National Institute for Fusion Science, Oroshi, Toki, Gifu 509-5292, Japan 68 National Institute for Fusion Science, Toki, 509-5292, Japan 69 National Institutes for Quantum and Radiological Science and Technology, Naka, Ibaraki 311-0193, Japan 70 National Technical University of Athens, Iroon Politechniou 9, 157 73 Zografou, Athens, Greece 71 NCSR ‘Demokritos’, 153 10, Agia Paraskevi Attikis, Greece 72 NRC Kurchatov Institute, 1 Kurchatov Square, Moscow 123182, Russian Federation 73 Oak Ridge National Laboratory, Oak Ridge, TN 37831-6169, United States of America 74 PELIN LLC, 27a, Gzhatskaya Ulitsa, Saint Petersburg, 195220, Russian Federation 75 Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Torino, Italy 76 Princeton Plasma Physics Laboratory, James Forrestal Campus, Princeton, NJ 08543, United States of America 77 Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, United States of America 78 SCK-CEN, Nuclear Research Centre, 2400 Mol, Belgium 79 Second University of Napoli, Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 80 Seoul National University, Shilim-Dong, Gwanak-Gu, Republic of Korea 81 Slovenian Fusion Association (SFA), Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia 82 Space and Plasma Physics, EES, KTH SE-100 44 Stockholm, Sweden 83 Technical University of Denmark, Department of Physics, Bldg 309, DK-2800 Kgs Lyngby, Denmark 84 The ‘Horia Hulubei’ National Institute for Physics and Nuclear Engineering, Magurele-Bucharest, Romania 85 The National Institute for Cryogenics and Isotopic Technology, Ramnicu Valcea, Romania 86 The National Institute for Laser, Plasma and Radiation Physics, Magurele-Bucharest, Romania 87 The National Institute for Optoelectronics, Magurele-Bucharest, Romania 88 Troitsk Insitute of Innovating and Thermonuclear Research (TRINITI), Troitsk 142190, Moscow Region, Russian Federation 89 University of Electronic Science and Technology of China, Chengdu, People’s Republic of China 90 Unità Tecnica Fusione, ENEA C. R. Frascati, via E. Fermi 45, 00044 Frascati (Roma), Italy 91 Universidad Complutense de Madrid, Madrid, Spain 92 Universidad de Sevilla, Sevilla, Spain 93 Universidad Nacional de Educación a Distancia, Madrid, Spain 94 Universidad Politécnica de Madrid, Grupo I2A2, Madrid, Spain 95 Università di Roma Tor Vergata, Via del Politecnico 1, Roma, Italy 96 University College Cork (UCC), Ireland 97 University Milano-Bicocca, piazza della Scienza 3, 20126 Milano, Italy 98 University of Basilicata, Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 99 University of California, 1111 Franklin St., Oakland, CA 94607, United States of America 100 University of Cassino, Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 101 University of Helsinki, PO Box 43, FI-00014 University of Helsinki, Finland 102 University of Innsbruck, Fusion@Österreichische Akademie der Wissenschaften (ÖAW), Innsbruck, Austria 103 University of Latvia, 19 Raina Blvd., Riga, LV 1586, Latvia 104 University of Lorraine, CNRS, UMR7198, YIJL, Nancy, France 105 University of Napoli ‘Federico II’, Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 106 University of Napoli Parthenope, Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 107 University of Texas at Austin, Institute for Fusion Studies, Austin, TX 78712, United States of America 108 University of Toyama, Toyama, 930-8555, Japan 109 University of Tuscia, DEIM, Via del Paradiso 47, 01100 Viterbo, Italy 110 University of York, Heslington, York YO10 5DD, United Kingdom 111 Vienna University of Technology, Fusion@Österreichische Akademie der Wissenschaften (ÖAW), Austria 112 VTT Technical Research Centre of Finland, PO Box 1000, FIN-02044 VTT, Finland 113 Wigner Research Centre for Physics, PO Box 49, H-1525 Budapest, Hungary Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 8 E-mail. xavier[email protected] Received 17 November 2016, revised 9 January 2017 Accepted for publication 30 January 2017 Published 15 June 2017 Abstract The 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at βN ~ 1.8 and n/nGW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed. Keywords: JET, plasma, fusion, ITER (Some figuresmay appear in colour only in the online journal) 1. Introduction The European nuclear fusion research community has elaborated a Roadmap to the realisation of fusion energy in which ‘ITER is the key facility and its success is the most important overarching objective of the programme’ [1]. In this overview paper, the contribution of the recent (2014–2016) JET experiments with the ITER first wall materials mix (e.g. [2–8]) and the underlying physics understanding with improved diagnostics are reviewed in the context of optimising the ITER Research Plan [9]. Indeed, together with the ITER scenario development for deuterium–tritium (D–T) operation [10–12], a strong focus on JET utilization is pursued for addressing ITER needs and developing a sound physics basis for the extrapolation through first principle and integrated modelling (e.g. [13, 14]), i.e. such as plasma–wall interaction, disruption mitigation taking benefit of the recent installation of a third disruption mitigation valve, L to H mode threshold scaling, core and edge confinement studies with metallic wall, specific ITER relevant scenario aspects, preparation of the ITER nonactive phase of operation (hydrogen campaign) etc. Recent progress addressing key issues for the supporting physics research programme accompanying ITER construction is reviewed in five main sectionsas follows: (i) Plasma–material interaction studies with ITER first wall materials (in section 2): The JET ITER-Like Wall experiment provides an insight in the coupling between tokamak-plasma operation and plasma–surface interaction in the unique beryllium and tungsten material environment and acts as a test-bed to verify plasma–wall interaction physics models and modelling tools for ITER. (ii) Disruption prediction and mitigation studies for ITER (in section 3): disruptions are considered as the highest programmatic risk in the ITER Research Plan and significant experimental and modelling effort in Europe and JET is reviewed. (iii) Physics studies of H-mode access and exit studies with ITER first wall materials (in section 4): high spatial resolution Doppler backscattering measurements and isotope scaling have recently revealed novel insights into the development of the edge transport barrier. These measurements are essential to validate the L–H transition theory and to improve predictions for ITER. In addition, strategies for controlled H-mode plasma termination for ITER have been developed and recently tested on JET. (iv) Access conditions to high confinement and ITER scenario development (in section 5): tokamak first wall materials affect plasma performance, even changing the confinement scaling. The operational constraints of a metal wall can prevent plasma energy confinement required for QD–T = 10 on ITER. Progress on JET to mitigate this risk and to understand the confinement modification due the change of the first wall materials is reported aiming at maximizing the core and pedestal performance in stationary condition with the tungsten divertor constrain. (v) Nuclear fusion technology in support of ITER (in section 6): The measured D–D neutron fluence and gamma dose rates have been successfully compared with simulations performed with the codes used for ITER nuclear analyses. This is an important step to gain confidence in ITER safety assessment calculations. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 15 full parallel heat flux while allowing direct spatially resolved observation of the top surface. This was rectified by the new sloped lamella (see figure7 (right)), where in the same observation geometry the IR camera system now views directly at the slope exposed to increased heat flux. The new geometry also results in a smaller temperature gradient on the top surface and reduced sensitivity of the analysis to the surface incidence angle of the magnetic field. In the recent 2016 experiments, reproducible 2 T/2.5 MA, 2 MW input power, 2 s lamella exposure, L-mode plasma discharges have been performed [61]. The heat load distribution is computed assuming the optical projection of the parallel heat flux which is determined by iteration comparing synthetic with experimental IR data as illustrated in figure8. With the improved calculation (figure 8), a fair agreement is obtained between the measured and simulated IR temper atures for three different lamella configurations: standard, sharp leading edge (from the 2013 experiment) and the new special protruding sloped lamella for the 2015/2016 experiment. In the recent 2016 experiments with the new lamella, the directly measured heat load no longer showed a discrepancy in L-mode to the value from geometric projection of the parallel power flux [61], in line with observations from companion experiments at other tokamaks (COMPASS [62] and ASDEX Upgrade [63]). Indeed, concur rently to all these experiments, the originally required ad-hoc assumption of a lower than geometrically deduced power flux could be also rectified for the initial JET transient melt study by improved analysis using a more sophisticated model (full 3D description of the plasma heat load and heat diffusion) for the simulation of the lamella’s thermal response [61, 64]. The new results greatly improved confidence in the models used for predictive simulations of the local heat load distribution and of transient melt motion required for the design of optimally shaped castellated ITER divertor target modules [65]. 2.5. Dust analysis and impact for ITER Comprehensive and systematic surveys of dust generated in tokamaks have been carried out in order to provide data needed in the licensing process of ITER [66, 67]. In ITER, dust can pose the following issues: (i) safety hazard in the case of loss- of-vacuum accidents, owing to the remobilization of respirable toxic or radioactive dust that has accumulated during operation, (ii) safety hazard in the case of loss-of-coolant accidents, owing to the explosion risk due to hydrogen production by the exothermic oxidation of metallic dust with steam, (iii) operational hazard owing to dust-generated impurities penetrating deep into the core plasma and leading to high radiation losses, (iv) degradation of in-vessel diagnostic components and malfunction of inspection tools, (v) compromise to PFC integrity, for instance by bridging the gaps of castellated PFCs and undermining their resistance to thermo-mechanical stresses. In ITER, the Be first wall is expected to be the main source of dust. ITER-relevant generation mechanisms can be roughly categorized in the following manner: (1) production under steady state conditions mainly delamination of re-deposited Be layers but also arcing, (2) production under transient conditions (unmitigated major disruptions, vertical displacement events, run-away electrons) mainly droplet splashing from molten layers and material ejection during deep melting but also surface cracking and destruction of deposited layers. In this context, the collection of dust and co-deposits in JET with the ITER-Like Wall are the most relevant information for ITER full-metal device (see figure9, various pictures of metal particles retrieved from JET during dust collection). Figure 7. View of the special lamella assembly in the modified divertor module and 3D thermal modelling. Left: leading edge lamella as in the 2013 experiment; right: new special sloped lamella for the 2015/2016 experiment to allow direct temperature measurement by the IR camera system mounted on the top of the machine. The lamella is 5.5 mm wide and the raised sectionis 20 mm long. Far left: reproduced from [58]. © 2015 EURATOM. Third from left: reproduced from [60]. © 2016 EUROfusion. Figure 8. Measured versus simulated (with improved modelling) IR temperatures for three different lamellas: standard, sharp leading edge (from the 2013 experiment) and the new special protruding sloped lamella for the 2015/2016 experiment—from [61]. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 16 Dust collection is performed by two methods: (a) localized sampling using sticky pads from W coated CFC divertor and Be limiter tiles; (b) vacuum cleaning of all divertor modules [22, 68–72]. The amount of loose dust removed by vacuum cleaning of the divertor during the shutdown phases after two main operation periods (2011–2012 and 2013–2014) was respectively 1.4 g (0.06 g m−2 normalised to the divertor surface) and 1.8 g (0.08 g m−2), i.e. over two orders of magnitude less than after the operation of JET with carbon wall which is a positive message for ITER safety issue [25, 69]. These results reveal that steady state dust production was significantly reduced as well as that shallow melting by transients did not create a large amount of Be droplets. It is worth noting that since dust remobilization exhibits a strong size selectivity [70, 71], the collected size distribution does not reflect the generated size distribution. Nevertheless, the quanti ties of collected dust in JET-ILW are small, these studies are crucial for ITER, because these are unique data from a full metal-wall with the ITER material mix [72]. These activities revealed that metal dust is mainly produced by flaking of the co-deposited layers and from W-coated tiles (which is of no relevance to ITER). In addition, a comprehensive analysis of the collected dust and divertor tiles has been carried out at the International Fusion Energy Research Centre (IFERC) in order to identify dust characteristics such as structures, mat erial components and hydrogen isotope retention [73]. In [68], evidence on the formation of two types of beryllium particles was presented: flakes of co-deposits and small droplets. These two types of beryllium-rich particles are of great importance for ITER. In the case of tungsten-based particles two main forms were found: agglomerates originating from the coatings and spheroids. From the ITER point of view, agglomerates are of secondary importance as no coated PFCs are planned. The determination of the exact structure and size of Be and W dust will also be useful for the development and benchmarking of codes simulating dust generation and transport. Melting experiments in JET have confirmed the formation of droplets for both Be and W tiles [59, 60, 72] and in situ imaging has already provided indication of the droplet sizes. The planned tile extraction will allow a more detailed documentation of the morphology. The injection velocity, angle and size provide initial conditions to dust transport codes, since the phenomena of droplet and dust generation are decoupled from the physics of their further transport. For the validity of modelling predictions for ITER concerning the dust life-time but also the final dust destination and the formation of accumulation sites, information on the initial size is particularly important since the physics of dust-wall impacts and sticking exhibit a strong size dependence [74, 75]. Progress has been made in the understanding of transient impurity events (TIEs), identified by a sharp increase in radiated power. A clear statistical correlation with disruptions was found, TIE occurrence is more probable during disruption-proceeding discharges [76]. Moreover, an excellent Figure 9. Examples of metal particles retrieved from JET during dust collection: (a) beryllium droplet; (b) nickel droplet covered by beryllium-rich co-deposit (from [79]); (c) beryllium droplet splashed on the surface of a test mirror located in the main chamber (from [79]); (d) tungsten spheroid with recrystallized surfaces, the broken shell reveals empty interior (from [68]). (a) Reproduced from [79]. CC BY-NC-ND 4.0. (d) Reproduced from [68]. © 2015 EURATOM. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 17 correlation between the TIE rate and dust detection by high resolution Thomson scattering suggests that TIEs are caused by dust. The overall picture is the following [73, 76]: during disruptions the dust inventory is re-distributed and consequently part of the dust population is loosely adhered to the PFCs at the beginning of sequent discharges. Such dust remobilizes and migrates in the plasma, where its ablation releases high-Z impurities. Finally, the impact of arcing and cracking co-deposits on dust formation and, consequently, on the performance of diagnostic components (i.e. metallic mirrors) has been addressed in [77–79]. The study has proven significant erosion by arcing and melting of coated mirrors. This result should give indication for ITER in the selection and design of diagnostic systems. 2.6. Divertor neutral modelling One of the most important systems in a fusion device is the particle exhaust system whose primary objective is density and impurity control as well as helium removal. The torus exhaust vacuum pumping system inherently couples the plasma core and edge conditions with the subdivertor neutral pressure. ITER will utilize cryopumps for plasma exhaust at subdivertor pressures in the range between 1 and 10 Pa for hydrogen plasmas [80]. These conditions translate to varying collisionality regimes in the subdivertor, described by the Knudsen number λ=KnL/ , i.e. the ratio of the mean free path to the characteristic length of the system . Thus, the exhausted gas is more likely to be in the continuum regime near the private-flux region (PFR), covering transitional flow in the subdivertor region and ending up in the free molecular flow regime inside the cryopumps [81]. The complexity of its description demands an integrated approach between plasma and vacuum particle dynamics. Particularly for the subdivertor system sophisticated neutral models should be implemented, which not only take into account the geometrical complexity of the ITER divertor but also the capability to describe the neutral–neutral interactions sufficiently well such that the transport coefficients, namely neutral viscosity and thermal conductivity are modelled in a realistic way. In the above framework, the most efficient and suitable numerical method for neutral particle modelling is the direct simulation Monte Carlo method (DSMC), which is a particle-based algorithm for the simulation of gases at the kinetic scale [82]. It solves the non-linear Boltzmann equation by simulating group of model particles that statistically mimic the behavior of real molecules. Typically, in the DSMC approach the simulation of large number of model particles are evolved in small time steps in which their free motion and collisions are uncoupled. Based on this approach, a novel divertor gas simulator code (DIVGAS) is capable of modelling complex neutral gas flows in a tokamak sub-divertor. For validation of the code, demonstration of its feasibility and general benchmark, experimental data from JET (L-mode plasma cases with the JET ITER-like wall configuration) are successfully replicated over a wide range of density. To be more specific, the pressure gauge readings taken in the subdivertor region, properly corrected for the influence of the low conductance connection pipe so as to get representative values for the subdivertor volume, are well described using EDGE2D- EIRENE calculations as boundary conditions on the plasma side [83]. Figure10 illustrates a typical example of a pressure plot calculated with the code including the cryopump domain. The new approach has been successfully applied in the European ITER Physics Programme to describe the ITER subdivertor region with the background plasma calculated by the fluid edge code package SOLPS (B2-EIRENE) [84]. DIVGAS was used to assess the neutral gas recirculation towards plasma and through the gaps behind the vertical targets. The use of DSMC for this kind of problems is first-of-its kind and is considered to be most innovative with an excellent perspective for future applications, in particular for high density detached scenarios as envisaged for DEMO. Following the validation at JET, the effort of benchmarking and testing the capability of DIVGAS code has been continued by modelling the JT60SA subdivertor [85] and, currently on the way, the DEMO particle exhaust system [86]. 3. Disruption prediction and mitigation studies for ITER Disruptions are considered as the highest programmatic risk in the ITER Research Plan which deserves significant experimental and modelling effort in Europe. The disruption mitigation system Figure 10. Geometrical representation of JET sub-divertor structure (cyan area, left) and a typical calculated pressure contour plot (right). Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 18 for ITER is presently in the design phase, with two main candidates: massive gas injection (MGI) and shattered pellet injection (SPI) [87]. The ITER disruption mitigation system is aiming at simultaneously: (i) the reduction of heat loads to prevent the PFC melting, (ii) the reduction of the electromagnetic forces in the invessel components and in the vacuum vessel itself, and, (iii) the avoidance or the mitigation of run-away electrons. In ITER, three upper port plugs are allocated for the installation of disruption mitigation system components as well as one equatorial port [87]. 3.1. Disruption experiments Disruption mitigation experiments carried out in different tokamaks have demonstrated the viability of massive gas injection to reduce the heat loads and electromagnetic forces. However, uncertainties in the thermal load mitigation efficiency exist due to toroidal and poloidal asymmetries in the radiation. On JET, a third Disruption Mitigation Valve (DMV) has been brought into operation since 2015, which together with the other two DMVs are at toroidal and poloidal locations mimicking the ITER set-up (figure 11). Mitigation by massive gas injection (MGI) is mandatory for JET operation, and, dedicated experiments have been carried out to address ITER relevant issues related to: (i) the effect of the poloidal location of massive gas injection on the efficiency of disruption mitigation; (ii) the reduction of the radiation asymmetries using an optimised combination of MGI [88–91]. Electromagnetic loads are the result of halo and eddy cur rents induced into the vessel structures. The dynamic vertical vessel forces following a MGI have been measured over a plasma current range up to 3.5 MA (for a given magnetic configuration in either low or high triangularity) for all three injection locations separately while the quantity of injected argon has been kept constant (figure 12 (left)) [88, 89]. Over the explored range of plasma current the unmitigated disruption force, which has been determined by deliberate test-VDEs (black line), has been reduced by 33%–40% with MGI injections (figure 12 (left)). The deduced vessel force scaling for each injector system indicates that the choice of the injection location or impurity gas (argon or neon) has no influence on the vessel force reduction and that the mitigation efficiency is not reduced when increasing the plasma current (up to 3.5 MA). The gas amount from the mid-plane injector has been varied at two plasma currents (1.5 MA and 2.0 MA) to determine the optimum impurity injection that is required to minimise the vertical force. A minimum of the disruption vessel force is found with a very low amount of injected impurity injection ( ≅ 1 × 1022 particles). The existence of the minimum is interpreted as a trade-off between two competitive effects: the increase of the forces induced by the eddy current with impurity injection (shorter current quench phase) while the vessel force due to the halo current is reduced. ITER is aiming at radiating at least 90% of the stored thermal energy for mitigating disruptions at high plasma energy content. Initial experiments at JET carried out with one injector on the top of the machine have resulted in a saturation of the radiated energy fraction with increasing impurity injection [91, 92]. In ohmic disruptions, the asymptotic radiation fraction is in the range of 80–85% integrated over the entire disruption and is decreasing with increased ratio of thermal to total energy inside the vessel, explored up to the ITER nominal value of about 0.5 [88–91]. It should be noted that this includes the radiation during all phases of the disruption and the achieved radiated energy during the thermal quench phase might be even lower. Similar saturation levels have been observed when using the other MGI at the top location but with a higher particle throughput (factor 2), or, the one located in the mid-plane. Saturation and therefore highest values of radiation fraction are achieved at relatively low injected impurity quantities ( ≅ 1–4 × 1021 particles injected before the current quench). However, at present it cannot be concluded, due to diagnostic limitations, whether the saturation level is significantly different from unity or whether it indicates insufficient radiative energy dissipation. Figure 11. Poloidal and toroidal cross-section of JET with the locations of the three massive gas injection valves and the horizontal (Prad,H) and vertical (Prad,V) bolometers. Reproduced with permission from [89]. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 19 Thermal quench mitigation through an increase of the radiated power fraction is feasible provided that uneven poloidal and/or toroidal distribution of the radiated power do not result in very large localised radiation that will locally enhance the thermal loads to the first wall [87]. The radiation asymmetry results from the presence of the MHD activity (n = 1 mode) and from the localised injection. This effect is enhanced or diminished depending on the relative location between the n = 1 mode island and the MGI-location (e.g. maximum radiation peaking occurs when the injection is done close to the O-point of the n = 1 mode) [93]. The toroidal distribution of the radiated power is characterised by a peaking factor: the ratio of the maximum radiation to the average radiation. With a single injection, it has been found that the toroidal peaking factor of the radiated power is up to 1.8, which could lead to shallow melting of the first wall in ITER. By optimising the massive gas injection combining two injectors this value has been reduced down to a very low level, i.e. 1.2 [88, 89]. This has been obtained by combining the impurity injection from the two top injectors separated toroidally by an angle of 180deg. The minimum in the radiation asymmetry is found by increasing the injected impurity level from one toroidal injector while the injection from the other is kept constant. Remarkably, in a very small range around 1.0 × 1022 injected argon atoms the asymmetry between the two bolometry measurements on JET (horizontal and vertical) at two toroidal locations almost vanishes as illustrated in figure 12 (right) [88, 89]. These experimental findings on JET support the choice of injection locations for the ITER-disruption mitigation system. 3.2. Disruption modelling First simulations of a D2 MGI-triggered disruption in a purely ohmic JET plasma have been performed with the 3D nonlinear MHD code, JOREK [94, 95]. The objective is to progress in the understanding of MGI-triggered disruptions by validating the model on a ‘simple’ case before applying it to more complicated situations like injecting high-Z impurities and to ITER. A purely diffusive equationfor describing the neutral density evolution including ionisation/recombination atomic physics process has been added in the fluid reduced MHD JOREK codes with 3D toroidal geometry treating X-point and SOL. The simulations indicate that the MGI gives rise to a localised over-density front that rapidly propagates in the parallel direction. To reproduce the experimental interferometric data it is assumed that not all the neutral gas enters into the plasma. The MGI also causes the consecutive growth of several magnetic island chains (mainly 2/1 and 3/2) and seeds the 1/1 internal kink mode in cases with q0 < 1. The O-points of all islands are located in front of the gas injection region (outer mid-plane), consistently with experimental observations performed with a set of saddle loops in ohmic JET plasma [91]. In a second phase, a continuous increase of the magnetic islands width leads to a formation of stochastic layer at the plasma edge and to a fast loss of the plasma thermal energy by thermal conduction along the stochastic field lines (see figure13). A burst of MHD activity and a peak in plasma (thermal quench) current take place at the same time as in the experiment when the assumed resistivity is approaching the Spitzer’s resistivity. However, the reduction of magnetic energy is much smaller than in the experiment. The simulated radiation is also much below the experimental level. As a consequence, the thermal quench is not quantitatively reproduced, and, it is likely that larger unstable current gradient, via a sharper cold front, would strengthen the MHD amplitude. Present model limitations are the assumption of a purely diffusive transport of neutrals and the absence of background impurities in the target plasmas that may contribute to the explanation of these discrepancies. To improve the simulation of the neutral gas penetration a new 1D radial fluid code, IMAGINE, has been recently developed and applied to the JET D2 MGI-triggered disruption and Figure 12. Left: vertical vessel force FV as function of plasma current squared in low triangularity configuration. The black represents the FV for unmitigated vertical displacement events. The dashed lines are the scaling derived from the corresponding data set for each injector. Right: measured radiation asymmetry deduced the horizontal (Prad,H) and vertical (Prad,V) bolometers defined as (Prad,V − Prad,H)/ (Prad,V + Prad,H) for dual injections as a function of Ar-amount from Top,S injector while the Ar injected from Top,L is kept constant. Left: reproduced with permission from [89]. Right: reproduced with permission from [88]. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 20 the run-away MGI mitigation experiments [96]. The approach that has been developed treats the neutral gas transport within the plasma background according to first principle convective equationsand includes ionization, recombination and charge exchange atomic processes for describing the interaction of the neutral fluid with the background plasmas. Indeed, it is found that plasma charge exchange and (to a smaller extent) recombination processes slow down the gas flow at the plasma edge and a shock wave propagates away from the plasma further braking and compressing the incoming gas. As a result, only a small fraction of the gas penetrates into the plasma, and, the time to reach the q = 2 surface (5–10 ms) estimated in the simulations that take into account these atomic processes becomes compatible with the experimental time, i.e. the thermal quench onset time (thermal quench is usually triggered when the cold front reaches q = 2 surface). Another important result related to the question of gas penetration is the unsuccessful attempt to suppress the run-away electrons beam after its formation using MGI on JET [94]. This result is of paramount importance for ITER as JET is the only tokamak where run-away beam suppression using MGI was found to be inefficient. Again, the simulations indicate that the run-away electrons beam is shielded by the surrounding cold plasma when its background density is large enough (typically 1020 m−3) to prevent the neutral gas penetration. The mechanism identified is the gas-plasma friction force due to charge exchange process which is proportional to the plasma background density. Indeed, at lower plasma background density (typically 1019 m−3) the gas penetrates up to the run-away beam. These simulations contribute to explain the difference between JET and ASDEX Upgrade or Tore Supra experiments performed at lower plasma background density where runaway electrons beam suppression is observed with MGI. To further investigate this process experiments have been initiated in view of varying the plasma background densities. In addition, it is foreseen to install during the 2016–2017 shutdown a new Shattered Pellet Injection system (within the frame of an international collaboration) to compare the gas penetration conditions and further elucidate the differences between JET, DIII-D and ASDEX Upgrade experiments in view of ITER extrapolation. 3.3. Disruption prediction A pre-requisite to trigger any mitigation scheme is to reliably predict in real-time the foreseen disruption event with sufficient anticipation time. The ITER requirement on the success rate will vary for the different operational phases, but is expected to be above 95% for high performance operation with high disruption loads. The detection time has to be longer than about 20–40 ms prior to the disruption to be compatible with the reaction time of the mitigation system. A typical disruption predictor is the amplitude of the locked mode signal: macroscopic instabilities start locking to the wall and the locked mode amplitudes increase during the slowing down of the plasma rotation. When this amplitude reaches a certain threshold (established beforehand), it is interpreted as high probability of an imminent disruption. This signal is used either to attempt a safe landing of the discharge or to trigger mitigation actions. However, a simple amplitude threshold of the locked mode signal does not deal satisfactorily with ITER required prediction rate. The amplitude of locked instabilities, likely magnetic islands, seen as precursors to disruptions has been studied using data from the JET, ASDEX Upgrade and COMPASS tokamaks [97]. It was found that the thermal quench, is triggered when the amplitude has reached a distinct level. This information is used to determine thresholds for simple disruption prediction schemes. To improve the success rate of disruption prediction, machine learning methods that fully exploit the time and frequency domain of the signals have been developed and applied to JET [98]. An Advanced Predictor Of DISruptions (APODIS) was set-up during the first ITER-like wall (ILW) campaign and it is working routinely in the JET real-time network [99]. APODIS was trained with more than 8000 JET discharges corresponding to carbon wall operations and it is being used during the ILW campaigns without any retraining since 2010. The initial result just after the first three ILW campaign (991 discharges) has shown Figure 13. JOREK simulation of a JET disruption triggered by massive gas injection showing stochastisation of the plasma configuration. Poloidal cross sectionof the electron temperature; electron density, current density and Poincaré plots for the JET pulse 868 87 at t = 5.7 ms after the massive gas injection, i.e. at the start of the thermal quench-from [95]. Reproduced from [95]. © IOP Publishing Ltd. All rights reserved. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 21 a success rate of 98.36% (with a warming time on average 426 ms prior to the disruption time) and a false alarm rate of 0.92% [100]. The requirement of a large database of disruptive discharges to train the predictor is not compatible with safe ITER and DEMO operations. Therefore, adaptive predictors have been proposed with high learning rates using a limited disruption database [101–104]. The strategy is to retrain the predictors on a wider database only after missed disruption detection. The most recent predictor developed in JET avoids the use of past discharges for training purposes [105, 106]. The objective is to learn in each discharge the non-disruptive behaviour, and, to trigger an alarm when an anomaly appears. The locked mode signal has been used to implement a first disruption predictor based on anomaly detections. A wavelet transform of the locked mode signal is used to retain simultaneously information from both time and frequency domains. Success rates are above 85% and false alarm rates are below 5%. This single signal predictor based on anomaly detection (SPAD) has a disruption detection rate above 85% and false alarm rate below 5% and has been compared not only with the classical locked mode predictor based on threshold (LMPT) but also with the initial APODIS without retraining since the first ILW campaign (figure 14). Figure14 shows the disruption detection success rate of the three predictors versus the warning time, i.e. the alarm detection time prior to the disruption time. SPAD has a higher disruption detection success rate and earlier detection time. SPAD is being installed in the JET real-time network [107]. The ongoing effort for improvement focuses particularly in the direction of reducing the dispersion of the warning time, at present too large to allow detailed adjustments of the mitigation strategies. To reach this objective it is necessary to adopt new approaches and use a combination of signals. Indeed, the information carried by the locked mode signal is already fully exploited by the new generation of predictors such as SPAD. The possible strategy consists of developing tools capable of classifying the type of disruption, using a nonlinear manifold learning method [108–111]. 4. Physics of H-mode access and exit studies with ITER first wall materials Access to type I ELMy H-mode operation is an important milestone in the ITER research plan already in the non-active ITER phase of operation. Indeed, H-mode access needs to be demonstrated: (i) to ensure a fast and risk-controlled path to early D–T operation in ITER, (ii) to timely assess the need for an external heating upgrade, (iii) to develop ELM control schemes and H-mode exit strategy. Based on current 0D scaling laws (e.g. in [112]), the most viable path for ITER during the non-active phase to access the type I ELMy H-mode is presently in helium plasmas. If H-modes can be achieved in hydrogen at much lower threshold with the ILW, compared to the carbon wall and to the existing scaling laws (e.g. by changing magnetic configuration), it will significantly impact the ITER research plan. Knowledge of the L–H threshold power is therefore critical to the optimization of the time sequence of the experimental programme towards D–T operation and availability of the ITER systems. In the active phase of ITER operation, the anticipated threshold power on ITER is 53 MW in deuterium and 43 MW in deuterium–tritium mixture (at a density of 5 × 1019m−3 at 5.3 T) and is extrapolated from a multi-machine scaling [112], based on density, magnetic field and machine size. Many hidden parameters are known to affect PL–H leading to large scatter (factor 4) in PL–H in the present database and induce considerable uncertainty in the extrapolation. Because the available external heating power on ITER (73 MW max) is only marginally above the expected threshold, there is an ongoing effort to understand the underlying physics behind these additional dependencies and to evaluate if any could be used to lower the power threshold on ITER and widen the operational space. 4.1. H-mode access for ITER Identical discharges with the Be/W wall in deuterium have shown a 25%–30% reduction of the L to H power threshold, PL–H, in ASDEX Upgrade and in JET with metallic PFCs and a minimum as function of density not observed in JET-Carbon wall (e.g. figure15) [113, 114]. Zeff is shown to be a potential candidate explaining a lower power threshold in JET-ILW when compared to JET-carbon wall [115]. Indeed, it has been demonstrated that the JET-C threshold can be recovered with nitrogen seeding [116]. In addition, the H-mode power threshold in JET-ILW is found to be sensitive to variations in main plasma shape [117], the divertor recycling pattern and the plasma current leading to significant differences (factor of two) compared to 0D scaling laws predictions. Better understanding of the physics causing the divertor configuration effect could potentially open up strategies to reduce PL–H on ITER [117, 118]. An increase in edge Er × B Figure 14. Disruption detection success rate versus warning time, i.e. predictor detection time prior to the disruption time. Three disruption predictor comparisons locked mode predictor threshold (LMPT), APODIS, SPAD (JET ILW campaigns with 566 unintentional disruptions and 1738 non-disruptive discharges). Reproduced with permission from [107]. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 22 shear through the SOL radial electric field Er is proposed as a mechanism to explain the divertor configuration effect on the L–H threshold [117, 118]. Observations on JET-ILW indicate that configurations with a strong inner/outer asymmetry in the divertor recycling pattern are beneficial for H-mode access at reduced power [117]. Experiments in JET in the ITER-like wall show a factor of two reduction of PLH in a configuration with the outer strike point on the horizontal tile (Horizontal Target configuration) compared to that with the outer strike point on the vertical target (Vertical Target configuration), observed in the high density branch where PLH increases with plasma density. With no significant difference between global parameters in these two magnetic configurations, it is concluded that the difference in PLH is related to a difference of plasma parameters in the scrape-off layer (SOL) and divertor. EDGE2D-EIRENE simulations reproduced a large difference in experimental target profiles, leading to a significant difference in radial electric field which, in turn, may influence plasma turbulence around the separatrix location via Er × B shear [118]. The difference in observed target temperature profiles indicates a more positive Er in the SOL for the Horizontal Target configuration, creating a higher shear in the outer part of the Er well, and the EDGE2D-EIRENE modelling supports these observations due to a difference in the recycling pattern of neutrals between the two configurations. In addition, as shown on figure15 a clear correlation between detachment of the inner divertor leg to create highly asymmetric divertor conditions and the L–H transition in the high density branch has been recently reported [117]. These results indicate a strong role of the SOL in the physics of the L–H transition. At the highest densities in the L–H threshold density scans, the detachment of the inner divertor will immediately trigger an L–H transition, which demonstrates that this state, associated with a higher SOL Er, is beneficial for H-mode access. The understanding of the physics behind this mechanism could open up prospects of lowering the L–H threshold on ITER through influencing the divertor and SOL conditions: for instance by creating a dense high recycling inner strike point and hot outer target to increase Er in the SOL. Subsequently, experiments have been conducted in 2014 and 2016 in hydrogen plasmas to investigate the isotope effect on PL–H in JET-ILW. It was found that PL–H is increased by a factor two in the high density branch as it was anticipated, but for the first time it has been observed that the minimum density value is shifted to higher density in experiments performed with ICRH only at 1.8 T/1.2–1.7 MA [119]. Comparison between the hydrogen and deuterium discharges show the transition occurs at similar values of stored energy and closely matched edge density and temperature profiles in the high density branch, but a higher edge temperature is required in the low density branch in hydrogen compared to deuterium. This points to a higher Er shear required to balance a higher mode growth rate. The different isotope effect at low and high density provides a challenging test for L–H theories. In addition, during the 2016 experiments, the depend ence of PL–H on the effective mass has been systematically investigated by scanning the H and D mixture (i.e. isotope ratio, nH/(nH + nD)) both the in low and high density branch of the L–H threshold [120]. It was unexpectedly found, that PL–H has a non-linear depend ence with the isotope ratio (for both the two density branches). PL–H is approximately constant over a broad range of H and D mixture 20% ⩽ nH/(nH + nD) ⩽ 80%, with a value which is approximately an averaged between pure hydrogen and pure deuterium plasma. This intermediate PL–H value rapidly decreases (respectively increases) towards the pure D (resp. H) threshold value in the extreme part of the curve 0% ⩽ nH/(nH + nD) ⩽ 20% (resp. 80% ⩽ nH/ (nH + nD) ⩽ 100%). We conclude that trace quanti ty of hydrogen in deuterium (or vice-versa) may leads to significant variation of the L–H threshold. In addition, we have also shown in preliminary JET experiments that an injection of a trace quantity of helium gas (below 10%) in hydrogen plasmas also leads to a reduction of the L–H threshold [120]. These Figure 15. L–H threshold power at 2.4 T/2 MA for two magnetic configuration (vertical and horizontal target blue stars and black triangles) and power threshold for detachment of the inner divertor leg in the horizontal target configuration (red triangles) [117]. The dashed line correspond to the ITPA scaling [112]. Figure 16. Stationary zonal flows in Ohmic conditions preceding the L–H transition at different densities (Ip = 2.5 MA, Bt = 3 T with a slow NBI power ramp to identify the transition): (a) Er profiles inferred from Doppler backscattering measurements. (b) Density profiles from reflectometer [120]. Reproduced from [121]. CC BY 3.0. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 23 results opens a new route for reducing PL–H in the ITER nonactive hydrogen phase by adding a small amount of non-active gas with a higher atomic mass (like helium) leading to a lower L–H threshold. This new approach needs further experimental and modelling invest igations. It should also be noted that injection of helium gas may modify the edge conditions (e.g. edge radiation, particle penetration) and their impacts on plasma performance should be further assessed in a near future. Finally, high spatial resolution Doppler backscattering measurements have revealed novel insights into the development of the edge transport barrier thanks to high spatial resolution measurements of the edge radial electric field, Er (figure 16). For the first time, fine-scale spatial structures in Er, well with a wave number krρi ≈ 0.4–0.8, consistent with stationary zonal flows (ZF) have been observed in a tokamak [120, 121]. These observations imply that stationary ZFs are crucial for the pedestal development in JET. The characteristics of the structures depend with density (figure 16), i.e. as density is increased, the fine-scale spatial structures have reduced amplitude, reduced wavelength and their region of existence moves outward. The zonal flow amplitude and wavelength both decrease with local collisionality, such that the zonal flow E × B shear increases. Above the minimum of the L–H transition power threshold dependence on density, the zonal flows are present during L mode and disappear following the H-mode transition, while below the minimum they are reduced below measurable amplitude during L mode, before the L–H transition. Edge density fluctuation and Er measurements at high and low densities provide insight to the non-monotonic behavior of PL–H with density. Differences in the development of the edge Er profile in the high and low density branches of the transition are also observed, which point to a role for momentum transport in transition dynamics and not just heat transport. After the transition in the high density branch, there is a clear drop in density fluctuation δn/n by 20%–30% in the Er well (whereas smaller change to density fluctuations in the low density branch is reported). The measurements are consistent with a fundamental difference in the turbulence regime in the two density branches [120]. These new measurements are essential to validate the L–H transition theory and improve ITER predictions. The L–H transition studies at JET have also revealed an n = 0, m = 1 magnetic oscillation, starting immediately at the L to H transition (called M-mode at JET) [122]. While the magnetic oscillation is present a weak ELM-less H-mode regime is obtained, with a clear increase of density and a weak electron temperature pedestal. The axisymmetric magnetic oscillation is dominantly up-down, and its typical frequency is ~1 kHz. Analysis of magnetic signatures of the so-called I-phase in ASDEX Upgrade [123] reports both similarities and differences between I-phase and M-mode. The frequency of the JET M-mode appears to scale with the poloidal Alfvén frequency: the mass dependency was confirmed in the comparison of hydrogen and deuterium ICRH heated plasmas, the density and current dependencies were studied in deuterium. The MHD oscillation is detected in the pedestal, and modulates particle and heat fluxes to the divertor target. All these results have direct implications for ITER to optim ize the operational window (density, magnetic and divertor configuration, effective impurity, plasma detachment and SOL conditions) for accessing the H-mode at reduced power. 4.2. H-mode exit for ITER Operation of tokamaks with tungsten plasma facing components in the H-mode confinement regime presents specific challenges regarding the control of the impurity concentration in the main plasma [124–128]. Lack of impurity control can lead to the loss of the H-mode, the radiative collapse of plasmas by W accumulation and increased disruptivity, which is detrimental to ITER operation [128, 129]. Control of W in H-mode plasmas requires, as a first step, the control of W production and its transport into the core plasma through the SOL and edge transport barrier. In addition, even when the concentration of W at the pedestal is kept at low levels, unfavourable core W transport can lead to its uncontrolled accumulation and to loss of the H-mode due increased radiation. Strategies have been developed in present JET experiments to avoid W accumulation in stationary phases of H-mode discharges by controlled ELM triggering to control the edge W density and central RF heating to prevent core accumulation [125, 127–129]. Such schemes are also expected to be effective in ITER, where strong core W accumulation is not expected to occur due to the low particle source provided by the 1 MeV negative-NBI injection, which is in agreement with H-mode experiments with low core source [128]. On the other hand, the control of W transport can be more challenging during the confinement transient phases between L-mode and H-mode and in particular in the transition from stationary H-mode to L-mode [130, 131]. During this phase the pedestal plasma density and temperature decrease as the input power is reduced. This leads to long-ELM free phases causing uncontrolled increase of the edge W density and peaking of the core density profile, which is favourable for impurity accumulation. To avoid this effect, an approach developed in present experiments consist in triggering a fast H–L transition to increase the W flux from the core to the plasma periphery. This approach is, however, not applicable to ITER high Q regimes due to the impossibility to suddenly stop the alpha heating, and, because the fast change in plasma energy would lead to direct contact of the plasma with the inner wall [128, 130]. Therefore a slow decrease of the plasma energy in H-mode termination is required, which is prone to W accumulation. In order to address W control issues in the H-mode termination phase a series of dedicated experiments have been performed at JET supported by integrated modelling, using the JINTRAC suite of codes [131, 132]. In these experiments several H-mode termination scenarios with constant plasma current have been explored including variation of the decrease of the power ramp rate, gas fuelling level, central ICRH heating with and without active ELM control by vertical kicks and pellets during the H-mode termination phase [131]. JET H-mode plasma termination scenario has been developed to mimic with a slow NBI power ramp-down the expected slow decrease of the plasma energy during the ITER termination phase due to alpha heating in ITER, and, to avoid plasma contact with the inner wall. The experimental Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 24 results demonstrate the key role of maintaining ELM control and ICRH heating to minimise the W concentration in the exit phase of H-modes with slow (ITER-like) ramp-down of the NBI power in JET. Without ELM control, long ELM free phases occur and W accumulation takes place despite the application of central ICRH heating. The required level of ELM control is achieved at JET through adjustment of gas fuelling level (unlikely to be effective in ITER) or by active ELM control. The latter scenario provides an integrated solution regarding the control of W concentration and plasma energy evolution in the termination of H-modes that can be readily extrapolated to the corresponding phase of 15 MA Q = 10 plasmas in ITER. Modelling of experimental results carried out with JINTRAC [132] has highlighted the importance of the effect of ELM control on particle transport and edge temperature screening. Without ELM control, the ratio in time-averaged particle versus heat diffusivities in the edge transport barrier is reduced, leading to an increase in ion density relative to the temperature gradients and enhanced inwards neoclassical W transport in the pedestal region. In addition, the dependence of neoclassical core W transport on NBI momentum and particle sources as well as ICRH-assisted heating were found to be crucial for the explanation of observed core W transport properties in the H-mode termination phase. The existing core transport models seem to appropriately reproduce the plasma evolution in general and the accumulation of W in particular in the termination phase of JET H-modes. The model assumptions may thus be adequate for the prediction of the W transport behaviour in the H-mode termination phase in ITER as shown in [133]. 4.3. H-mode density limit In order to understand the mechanisms for the back trans ition to L-mode confinement at high density, the so-called H-mode density limit, systematic experimental invest igations have been performed on JET-ILW by increasing either the deuterium or hydrogen neutral gas fuelling injected from the plasma periphery [134, 135]. The various phases when increasing the density towards the H-mode density limit in deuterium or in hydrogen plasmas are as follow: a stable H-mode regime followed by a degraded H-mode phase, then, a reduction of the H-mode confinement with a dithering cycling phase that ends with a back transition to L-mode edge. We found that the density limit is not related to an inward collapse of the hot core plasma due to an overcooling of the plasma periphery by radiation. Indeed, the total radiated power as well as the radiation power in the main chamber stays almost constant during the H-mode phase until the H to L-back transition. We also found, by comparing similar discharges but fuelled with either deuterium or hydrogen, that the H-mode density limit exhibits a dependence on the isotope mass: the density limit is up to 35% higher in deuterium compared to similar hydrogen plasma conditions. In addition, the density limit is nearly independent of the applied power either in deuterium or hydrogen fuelling conditions. The H-mode density limits measured in various experimental conditions normalised to the Greenwald density are found to be consistent with the predicted values derived from a heuristic model based on the SOL pressure threshold of an MHD instability as recently proposed by Goldston [136, 137]. When applying this model validated on JET-ILW to ITER, the H-mode density limit is estimated to be close to the Greenwald density in ITER D–T operation. To summarise the JET results on the H-mode formation (section 4.1) and back transition to L-mode at high density, we conclude that the JET and ITER operational domains are significantly broaden when increasing the plasma effective mass (e.g. tritium or deuterium–tritium operation), i.e. the L to H power threshold is reduced whereas the density limit for the L-mode back transition is increased. 5. Access conditions to high confinement and ITER scenario development Tokamak first wall materials affect plasma performance, even changing confinement scaling. The operational constraints of a metal wall can prevent reaching plasma energy confinement required for the achievement of QD–T = 10 on ITER. To gain physics insight, dimensionless physics parameters scans have been performed in low triangularity baseline plasmas. In the course of the JET D–T scenario preparation, a major effort is made to maximise the core and pedestal performance in stationary condition while controlling the divertor surface temperature via strike points sweeping or/and extrinsic impurity seeding focusing on two ITER scenarios, i.e. baseline and hybrid H-mode of operation. Specific ITER relevant scenario aspects (e.g. real time control of divertor detachment, ICRH scenarios, fueling) are reported. 5.1. Thermal core and pedestal confinement with ITER-like wall 5.1.1. Global and core confinement. After the replacement of the plasma facing components, the global energy confinement of JET plasmas was often found lower compared to similar plasmas in the carbon wall configuration, particularly when scenarios were not properly optimized [138]. These observations have a direct impact on the extrapolation to ITER plasma performance. It is therefore important to find the cause for this deterioration. As the electron temperature at the top of the pedestal is lower in the ITER-like wall configuration, it is not obvious whether the decrease in core temperature is only due to the degradation of the edge confinement or if the core confinement itself has also been degraded. In order to address this question, a systematic interpretative heat transport analysis has been carried out where 10 pairs of ‘similar’ discharges for the two walls configuration have been selected (i.e. 10 carbon wall discharges and 10 corresponding ITER-like wall discharges). Among the baseline ELMy H-mode plasmas obtained in C-wall at normalised beta below two, the ILW counterpart discharges have been carefully selected to match the time-averaged value of the global plasma parameters, i.e. Ip, Bt, PNBI, ne , q95, and δ [139]. Figure17 (left) and (right) Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 31 [192]. The T–(9Be)–D scenario could be tested in future D–T experiments in JET-ILW plasmas to check if the intrinsic level of 9Be impurities is sufficiently low (~1%) for this newly proposed ITER scenario to be efficient. 5.4. High-triangularity H-mode operation with JET-ILW Achievement of high confinement at high density is a necessary condition for reaching the ITER target of QD–T = 10 (HIPB98(y,2) = 1, βN = 1.8 and ne/nGw = 0.85) [193]. High performance H-mode operation at high density strongly relies on the improved edge stability provided by higher plasma shaping. In the case of JET with the C-wall, it was found that high confinement quality (HIPB98(y,2) = 0.9–1) could be maintained at high density (ne/nGW ⩾ 1) in highly shaped plasma (δav ⩾ 0.4) [194] and this was linked with access to the mixed type I/Type II ELMy regime. On the other hand, past experiments in JET with the ILW in 2012–2014 showed that the high puff rates (>1022 D s−1) used to keep W core radiation within acceptable limits in the ELMy H-mode baseline scenario at high-δ (δav ~ 0.4, Ip = 2.5 MA) resulted in a confinement deterioration larger (10–30%) than that observed with the C-wall for similar conditions [138]. Those earlier experiments did not show positive effect of triangularity on global confinement [138]. Only by using nitrogen seeding it was possible to partially recover the confinement at high-δ [140, 167, 195, 196]. The reduced confinement of the high-density H-mode plasmas at high-δ remains one of the least understood results in JET after the change of wall materials. Since a high-δ shape is the reference shape for ITER [193], it is important to identify the physics elements that are limiting the pedestal/core confinement of high-δ plasmas in JET-ILW [197]. Recent 2015–2016 experiments on JET [197] have been conducted using a newly developed high-δ configuration (δav = 0.39) with a divertor geometry optimized for pumping (figure 24 (left)), with both strike points located in the divertor corners (building on the low δ results where confinement is optimised with optimised pumping [198]). In these experiments figure 23 (middle), high confinement H-mode plasmas have been sustained at high triangularity up to 2 MA/2.2 T during 5 s confirming that divertor pumping is a key element to improve confinement in ILW scenarios. These new results represent a significant progess with respect to earlier JET-ILW experimental campaigns [140], where the access to good confinement at high triangularity was restricted to low plasma current discharges (1.4 MA/1.7 T, βN ~ 2–3) [167] that typically operate at lower gas injection rates. In optimum pumping conditions, higher pedestal temperatures and pressures (lower collisionality) are obtained at higher triangularity in agreement with edge stability predictions. Higher pedestal temperature via profile stiffness lead to an increase of the total plasma pressure and stable discharges with HIPB98(y,2) ~ 0.9–1 and βN ~ 1.8–2 are now routinely obtained for both plasma shapes at 2 MA but at ne,ped/nGW ~ 0.5 (figure 24 (right)). The density profile of the high-δ discharges remains rather flat, thus the improved confinement is clearly a pedestal effect. This result highlights the importance of operating at low collisionality (high edge current) to recover the beneficial effects of triangularity on pedestal stability when approaching the Peeling-Ballooning limit. However, in contrast to results in JET-C, increasing the gas injection rate to operate at ne,ped/nGW > 0.5 leads to significant (~20%) confinement deterioration (figure 24 (right)) and a higher fELM (up to ~100 Hz), but no signature of the type I/II ELMy regime was found. The differences found between JET-C and JET-ILW H-mode plasmas suggests that the change in wall materials has strongly affected the divertor recycling/radiation patterns in gas fuelled JET-ILW H-mode plasmas, although the mechanism responsible of the observed differences in pedestal confinement has so-far not been identified. 5.5. JET prospects for D–T operation One of the main objectives of the coming deuterium and deuterium–tritium campaigns is to extend the performance Figure 24. Left: plasma shapes at low and high triangularities with magnetic configurations optimised for divertor pumping; approximate location of the cryopump is indicated; (middle) HIPB98(y,2) Improved confinement factors for low-(square) and high-δ plasmas (closed blacks circles) (2 MA/2.2 T) corresponding to a gas scan at fixed input power (P/PL–H = 2). Data at 2 MA from previous campaigns (before 2014) in light orange circles; (right) βN versus pedestal density normalized to Greenwald density limit ne,ped/nGW from 2015/2016 experiment but with different magnetic configuration. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 32 of the ILW at higher plasma current (>2.5 MA) by fully exploiting the JET machine capability at high additional powers in the range of 40 MW with up to 34 MW of NBI power and 6 MW ICRH [4, 5, 12]. The quantitative 0D, high level objective is to reach deuterium plasma scenarios with thermal energy content of the order of Wth(D–D) ~ 12 MJ with HIPB98(y,2) ⩾ 1 generating a stationary fusion D–D neutron rates of RD–D ~ 6 × 1016 n s−1 (around 15 MW of fusion power) during 5 s [5, 12]. To reach these objectives, two main approaches are being pursued at low triangularity configuration [11, 167], i.e. (i) the ITER baseline scenario by simultaneously increasing the current, toroidal field and applied powers at q95 ~ 3 and βN ~ 1.8–2, (ii) the ITER hybrid scenario at slightly reduced plasma current and higher q95 ~ 3–4 but at βN > 2 to enter in the virtuous cycle where confinement is increased at high beta through the interplay between the core and edge confinement optimisation [167]. With the available applied power in the range of 26–30 MW, the JET performance has been recovered up to a plasma current of 2.5 MA for both the ITER baseline and hybrid scenarios [11]. As part of the scenario development it is also essential for JET and ITER that attention is given to minimize the occurrence of disruptions close to full performance, by developing disruption avoidance techniques [199]. With the goal of simultaneously increasing the fusion performance while controlling the core W content, a dual frequency ICRH heating scheme has been recently explored using both the H and 3He minority heating schemes optimising respectively the electron and ion minority heating [200]. These initial tests were conducted in H-mode at a magn etic field Bo = 3.4 T and plasma current Ip = 2 MA with typically 15 MW of neutral beam power and 6 MW of total ICRH power at 51 MHz (on–axis H minority) and 33 MHz (on-axis 3He minority), of which up to 2 MW were delivered by the ITER-like antenna [201]. In this promising scenario, the lowest bulk radiation with the highest ion temperatures was obtained in the dual frequency ICRH heating compared to the pure H-minority scheme. The challenge is to reach and sustain the fusion performance while not exceeding the power and energy limits imposed by the inertially cooled W-divertor. In this context, ITER relevant real time divertor detachment control algorithms have been tested on JET [202, 203]. Since Langmuir probes are expected to be part of the ITER divertor diagnostics, this opens possibility to control the divertor target power density through the control of the detachment level using the measured probes saturation current (Isat). In order to provide a proof of principle experiments for ITER, new real-time detachment control algorithms have been successfully implemented and qualified on JET in type-I ELMy H-mode regime [202] (see figure25 as an illustration). The degree of divertor detachment conditions has been maintained in real time control conditions through the seeding of radiative extrinsic impurities as actuator (e.g. nitrogen seeding in this proof of principle experiment), and, as a sensor the measurements of the saturation current of the divertor Langmuir probes have been utilized [202]. The level of divertor detachment is calculated in real-time by comparing the outer target saturation current measurements to its value at the roll-over (Iroll) (figure 25). The algorithm recently developed at JET is able to control the degree of detachment with either fix or swept divertor strike point in horizontal outer target divertor configuration. In addition, it has been shown that the roll-over conditions for the detachment is found automatically if the control starts in attached divertor conditions. It has also been demonstrated that the gains of the controller are automatically adapted in real-time to avoid oscillations of the controlled system. This control is useful for JET operations with impurity seeding and could be coupled with other real-time controllers such as X-point sweeping to spread the heat load on the divertor tiles and/or real time ELMs control by injecting deuterium neutral gas [202]. Following the success of these first attempts, other tests are foreseen in different divertor configuration (vertical targets) and also with other Figure 25. ITER relevant real time divertor detachment control for two levels of detachment references in two JET discharges #90517 (left) and #90519 (right) (Bt = 2.2 T/Ip = 2 MA, low triangularity configuration). For each figure, time evolution of the nitrogen injection level (top box), and (bottom box) real-time level of attachment (Isat/Iroll) (blue curve) with pre-roll-over request (green curve) and post-roll- over request (red curve). Reproduced from [202]. © 2017 EUROfusion Universidade de Lisboa Instituto Superior Tecnic. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 33 impurities like Ne, Ar or CD4. This reliable and simple system tested in JET could be one of the options for real-time detachment control to be transferred on ITER provided that reliable Langmuir probes will be installed in the divertor. In addition to the experimental development, a significant modelling program has been initiated with the aim of optimizing the path towards sustained fusion energy production in deuterium–tritium (D–T) [175, 204]. D–T projection of the expected fusion performance has been first calculated based on present plasma scenario but assuming that the experimental profiles and confinement enhancement factors could be translated at higher field, current and applied powers (i.e. temperature and density profile shapes are kept constant with a fixed ratio of the density normalised to Greenwald density when increasing the plasma current). With these assumptions the predicted fusion performance is 7.5 MW for the baseline scenario (at HIPB98(y,2) = 0.8) at high current (4.5 MA) and 13 MW for the hybrid regimes with 40 MW of applied power at lower current (2.5–3.0 MA). To complement this simple prediction, more sophisticated time dependent integrated scenarios modelling have been performed [175] using Trap Gyro-Landau Fluid (TGLF) model [205] for the core transport validated on the JET database [204]. For that purpose, high beta domain has been chosen for its optimization due to its low power degradation obtained in low gas conditions, something beneficial for maximizing the fusion power at high input power [167]. An optimum plasma operational point, in terms of electron density, has been found due to the good penetration of the NBI power at reduced average density [176]. More importantly, the impact on turbulence and on fusion power of the effective mass change from D–D to D–T [175] has been explored by performing simulations at maximum power and including D and T species in TGLF model. With exactly the same external heating source profiles (without including the alpha-heating effect to single out the isotope effect on transport modelling), both ion and electron temperatures show a significant increase from D–D to D–T mixtures when including the isotope effect on core transport in TGLF, especially strong for the ion channel (figure 26). This is due to a stronger turbulence stabilization of core turbulence in D–T than in D–D, which also leads to an increase of density peaking for D–T. Therefore, the equivalent fusion power also significantly increases in D–T when including the effective mass change on transport, from Pfus ≅ 11 MW to 16 MW. A simple explanation has been proposed by taking into account the mass effect in the effectiveness of the E × B flow shear for quenching ITG transport (it scales as the square root of the ion mass) and has been confirmed by performing D–D and D–T simulations with and without ExB flow shear stabilization [175]. The isotope effect has also been analyzed by performing gyro-kinetic simulations with the GENE code for the ITER hybrid scenario including kinetic electrons, collisions, electromagnetic effects and up to five species [206]. It is found that the interplay between nonlinear micro-turbulence effects generate an isotope effect leading to a change of the ion heat fluxes from D–D to D–T plasmas. In this context, one of the objectives of the future pure JET tritium campaign, foreseen in 2018, will be to investigate the hydrogen isotope effects on the core and pedestal confinement, on the L to H transition and on ELM physics. Regarding alpha power effects, the simulation indicates that the fusion power generated should have a noticeable impact on the fast ion generation and electron heating in regimes without sawteeth activities [207]. This will allow the analysis of Toroidal Alfvén Eigenmodes (TAE) stability and the impact on turbulence reduction [208]. This opens up the possibility of analyzing already at JET some key physics issues expected in ITER nuclear active phase of operation, such as the impact of alphas fast ion pressure, electron heating on tungsten impurity transport, fast ion confinement and neutron yield production [209]. 6. Nuclear fusion technology in support of ITER Significant effort and results have been obtained recently within the JET programme in the field of nuclear fusion technology in support of ITER [5, 211–214], i.e. neutronics, neutron induced activation and damage ITER materials, nuclear safety, tritium cycle, nuclear waste production and characterization. 6.1. Neutronics and code validation The 14MeV neutron rates issued from the D–T fusion reaction should be accurately measured for the scientific exploitation of the JET and ITER D–T experiment (code validation, performance optimisation), for the accurate measurement of the fusion power (including tritium burn and tritium accountancy), and, for a precise estimate of the machine activation within the available neutron limit. On JET, an accurate calibration procedure of neutron detectors at 14 MeV neutron energy (235U fission chambers and the in-vessel activation system) Figure 26. Comparison between the electron and ion temperatures obtained with TGLF transport model for D–D and D–T mixtures with otherwise identical settings (no credit for alpha power). JET Projection at 2.5 MA/2.9 T/40 MW volume averaged density of 3.9 × 1019m−3. Reproduced from [175]. © IOP Publishing Ltd. All rights reserved. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 34 has been developed to measure the fusion power during the future D–T experiments. The 14 MeV neutron calibration is designed using a 14 MeV neutron generator to be deployed in JET by remote handling. The calibration layout and strategy have been developed taking into account the source characteristics, the safety requirements and the limitations imposed by the remote handling capabilities. As a calibration source, the neutron generator must be fully characterized, in terms of neutron energy spectrum and anisotropy of neutron emission, and absolutely calibrated. As it cannot be considered a stable source, its neutron emission rate during the in-vessel calibration has to be continuously monitored using more than one monitoring detectors which, in turn, have to be absolutely calibrated. Two 14 MeV neutron generator units (~2 · 108 n s−1) and the power supply/control unit were purchased and delivered in October 2015. Both units have been fully characterized during two experimental campaigns at a dedicated neutron facility (the National Physics Laboratory, NPL, Teddington, UK) that took place in November 2015 and June 2016: emission rates at many different angles, neutron spectra at several different angles, stability of the monitoring detectors attached to the neutron generators were measured using several neutron detection and spectroscopy techniques. The count rate of monitoring detectors has been related to the neutron generator absolute intensity as well. The deployment of the D–T neutron generator inside the JET vacuum chamber in different toroidal and poloidal positions will take place in the 2016–2017 shutdown. The operation time required for the neutron generator in each position is in the range 0.3–4 h during which the neutron emission rate by the generator will be provided by the monitoring detectors. Extensive neutronics modelling of the neutron generators/detectors and of the JET machine are required to provide the characterization and the calibration of the neutron generators, and to derive the response of JET neutron monitors to the neutron D–T plasma source at the required accuracy level. The JET calibration strategy is an important step to benchmark the calibration procedure for ITER where neutron detectors have to provide the fusion power (10% accuracy) and the amount of T-burnt for T-accountancy. Dedicated neutron measurements around JET have been performed to validate the various codes used in ITER to predict quantities such as the neutron flux along streaming paths, the activation of materials, as well as the resulting shutdown dose rates [212, 213]. For this purpose, several streaming experiments have been carried out, consisting of measuring the neutron fluence and dose-rates in the torus hall and along its ducts. It was demonstrated that the neutron fluence measurements along penetrations of the JET torus hall biological shield are well reproduced by the Monte-Carlo codes over six orders of magnitude of the neutron fluence as shown in figure27 and reported in [211]. Calculations have been carried out using ITER relevant Monte-Carlo codes such as MCNP, a validated geometrical model of JET and neutron cross-section data from the ITER reference nuclear data library (FENDL- 3). Benchmark against the AutomateD VAriaNce reducTion Generator (ADVANTG) software, which generates variance reduction parameters for Monte Carlo simulations and which is now increasingly used in ITER to speed up neutronics analyses, has also been performed showing a good agreement between this code and the full MCNP calculations. Shutdown dose rates have been also calculated with various codes (Advanced D1S, R2Smesh, MCR2S and R2S-UNED). A good agreement is found among the codes that reproduce the measured gamma dose rates along the mid-port and in several cells outside the vessel. The measured D–D neutron fluence and gamma dose rates have been compared with simulations performed with the codes used for ITER nuclear analyses. A good agreement is obtained which is an important step to gain confidence in ITER safety assessment calculations [212, 213]. 6.2. Tritium fuel cycle and detritiation Up to the start of ITER operation, JET is the only tritium compatible magnetic confinement fusion device currently active. The active gas handling system, AGHS, was constructed to process and recycle the gases from the torus and Neutral Beam Injectors [214]. The tritium facility is located in a separate building equipped with its own ventilation system and connected with the JET torus via gas transfer and pumping lines. The AGHS is presently being upgraded with the possibility of using four Gas Injection Modules (GIMs) instead of one used in the previous D–T campaign (1997), with an improved T-accountancy and a new water detritiation system to fully close the tritium fuel cycle at JET [215]. This GIM upgrade will ease the transfer from deuterium to tritium plasma scenarios initially developed using different GIMs and will provide a better control of the D–T mix within the JET plasmas. There is also a requirement to improve our tritium accountancy techniques to allow the quantities of tritium being transferred to, and returning from, the JET machine to be accurately traced at a level below 1%. The first steps have been made to improve the tritium accountancy with an upgrade of the Figure 27. Comparison between measured and calculated neutron fluence along two penetrations through the JET Torus Hall biological shield: the access labyrinth and the air duct chimney [211]. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 35 instrumentation for tritium measurement, e.g. by the development of a solid state based detector. The AGHS exhaust detritiation system produces tritiated water at a rate averaging 9200 litres per year. This is collected in a tank and stored in stainless steel drums. These drums have historically been shipped to the Ontario Power Generation Inc. in Canada for disposal and recycling. However, it has been decided that an on-site water detritiation system will be constructed to allow the processing of tritiated water and the recovery of contained tritium. The tritium recovered from the water will be fed back into the AGHS plant for processing (figure 28). The water detritiation system is designed to have an annual throughput of approximately 15 000 kg with activities of up to 200 GBq l−1. It is planned to start non-active commissioning of the water detritiation system by 2016. The valuable experience gained both in the preparation and the execution of the JET tritium and D–T experimental campaigns at JET is contributing to train the future ITER operator of the Tritium plant in terms of operation and maintenance and will provide quantitative information for the nuclear regulator, e.g. radioactive waste management contaminated with tritium. 6.3. Nuclear waste production and characterization JET operations generate large quantities of waste, some of which radioactive and contaminated with tritium. Moreover, as beryllium is used in the ITER-like Wall, it is assumed to be present within all type of solid waste. ITER is interested in any information from JET experience that may help with aspects of ITER waste production and characterization in order to establish the routes for the subsequent decontamination and the available disposal routes. In this context, activity has been carried out to validate the tools and processes required by ITER [216]. 7. Prospects and conclusion The JET tokamak and its surrounding technology facilities have a number of features that are presently unique: possibility to operate with all hydrogen isotopes, ITER-like wall, tritium and beryllium handling facilities, remote maintenance facility. We have shown that the operation of these facilities could play an important role in optimising the ITER research plan and thereby in ensuring a rapid transition from ITER first plasma to ITER D–T operation. Indeed, recent analysis of the ITER research plan has focussed on maintaining the shortest achievable path to D–T operation and the achievement of the QD–T = 10 milestone. In this context, the exploitation of all metal plasma facing components facilities will support this important challenge during both the non-active and active ITER operation. We conclude that the underlying physics understanding of the JET ITER like wall operation and results requires developing an integrated vision where the science of the wall mat erials, plasma surface interaction, scrape-off layer, pedestal and plasma core physics are strongly coupled and interconnected. A sound scientific based extrapolation of the JET results towards ITER and future reactor (DEMO) operation will require a new paradigm to be developed inter-linking these various physics processes beyond a simple empirical scaling extrapolation. Up to 2020114, the focus of the JET campaigns is the preparation of the deuterium, tritium and D–T campaigns and the investigation the hydrogen isotope effects on fusion performance with the ITER material mix. Both baseline and hybrid operational regimes should progress towards ITER dimensionless parameters (H-factor, beta, ρ*, ν* etc.) leading to stationary fusion performance, while remaining compatible with the ILW. After the 2016–2017 shutdown, the major challenge for the 2018–2019 experimental campaigns consists of integrating high confinement operation with the divertor constraints at full applied heating power. During the 2016–2017 shutdown, in addition to the installation of the Shattered Pellet Injector for ITER relevant disruption experiments, it is foreseen to upgrade the actively cooled components of the NBI system that exhaust the heat load from non-dissociated + D2 ions [5]. When these new components will be installed, the NBI system will be capable in providing steady 34 MW during at least 5 s in a reliable manner in either deuterium or tritium [5]. Therefore, one of the main objectives of the next deuterium campaigns are to further extend the performance of the ILW by fully exploiting the JET machine capability at high additional powers in the range of 40 MW with up to 34 MW of NBI and 6 MW of ICRH powers. The quantitative objective is to reach stationary deuterium plasma scenarios in 2018/2019 with thermal energy content of the order of Wth(D–D) ~ 12 MJ with HIPB98(y,2) ⩾ 1. Then it is foreseen, to assess the transferability of the developed scenarios when varying the plasma isotope content from deuterium to tritium before the D–T campaigns in 2019. The D–T campaign will provide an integrated test of fusion technology and ITER scenarios with the ITER mat erial mix including the isotope effects on confinement, alpha physics, L–H threshold, ELM and pedestal physics. In parallel, it has also been proposed to extend the life of JET beyond 2020 as an ITER test-bed facility until the start of the scientific exploitation of ITER [15]. After a number of enhancements and refurbishments the JET device will be even Figure 28. Sketch of the JET tritium cycle with the new water detritiation system where tritium waste will be re-processed and recovered to close the on-site tritium cycle [215]. Reprinted from [215], Copyright 2015, with permission from Elsevier. 114 Pending decisions on funding EUROfusion and the JET Operating Contract in 2019–2020. Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 36 more suited to perform risk mitigation experiments for ITER and to train the ITER operation staff [15]. To make JET even more relevant for ITER, a number of enhancements (hardware and software) have been proposed and extensive feasibility studies have been performed for a 10 MW Electron Cyclotron Resonant Heating system at the ITER frequency (170 GHz) [217], a better diagnosed and more ITER-like divertor upgrade [218] and Resonant Magnetic Perturbation Coils [219]. In addition, it is proposed that JET becomes a test bed to develop and demonstrate real time control concepts for ITER using identical algorithms and software. In this context, it is proposed to upgrade the existing real-time control system to a new system, based on more powerful hardware and software architecture. The primary goal of such an extension and set of upgrades would be to prepare for integrated ITER operation with the ITER control tools (actuators and real time plasma controllers), with the ITER mix of materials for the first wall using the ITER modelling tools for experiment preparation and analysis [220]. Acknowledgment The corresponding author would like to warmly acknowledge the impressive collective work of the JET Task Force Leaders, the JET Project Leaders, the JET contributors, the JET operator, the JET Exploitation Unit and the EUROfusion Programme Management Unit for achieving the scientific results reported in this overview paper. In addition, the corresponding author would like to acknowledge valuable scientific discussions and inputs from the JET international partners, and, in particular from his colleagues at ITER Organization Central Team. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. References [1] RomanelliF., BarabaschiP., BorbaD., FedericiG., HortonL., NeuR., StorkD. and ZohmH. 2012 Fusion Electricity: a Roadmap to the Realisation of Fusion Energy (Culham/ Garching: EFDA) [2] PamelaJ., MatthewsG.F., PhilippsV., KamendjeR. and JET-EFDA Contributors 2007 An ITER-like wall for JET J.Nucl. Mater. 363–51 [3] MatthewsG.F. etal 2011 JET ITER-like wall—overview and experimental programme Phys. Scr. T145014001 [4] RomanelliF. and JET Contributors 2015 Overview of the JET results Nucl. Fusion 55104001 [5] HortonL. etal 2015 Operation of JET with an ITER-like wall Fusion Eng. Des. 96–728 [6] MatthewsG.F. etal 2013 Plasma operation with an all metal first-wall: comparison of an ITER-like wall with a carbon wall in JET J. Nucl. Mater. 438S2 [7] BrezinsekS. etal 2013 Fuel retention studies with the ITER- like wall in JET Nucl. Fusion 53083023 [8] MatthewsG.F. etal 2014 The second phase of JET operation with the ITER-like wall Phys. Scr. T159014015 [9] CampbellD.J. and ITER Collaborators 2012 Challenges in burning plasma physics: the ITER research plan Proc. 24th Int. Conf. on Fusion Energy (San Diego, USA, 2012) (Vienna: IAEA) ITR/P1-18 (www-naweb.iaea.org/napc/ physics/FEC/FEC2012/index.htm) [10] HortonL. etal 2016 JET experiments with tritium and deuterium–tritium mixtures Fusion Eng. Des. 109–11925 [11] NunesI. etal 2016 Plasma confinement at JET Plasma Phys. Control. Fusion 58014034 [12] LitaudonX. etal 2016 JET program for closing gaps to fusion energy IEEE Trans. Plasma Sci. 441481 [13] FalchettoG.L. etal 2016 EUROfusion Integrated Modelling (EU-IM) capabilities and selected physics applications Preprint: 2016IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) TH/P2-13 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) [14] LitaudonX. etal 2013 Modelling of hybrid scenario: from present-day experiments towards ITER Nucl. Fusion 53073024 [15] DonnéA.J.H., CowleyS., JonesT. and LitaudonX. 2016 JET contributors Risk mitigation for ITER by a prolonged and joint international operation of JET J Fusion Energy 3585 [16] WiddowsonA.M. etal 2016 Overview of the JET ITER-like wall divertor Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy) (toappear) [17] MayerM. etal 2016 Erosion and deposition in the JET divertor during the first ILW campaign Phys. Scr. T167014051 [18] NeuR.L. etal 2014 Experiences with tungsten plasma facing components in ASDEX UPGRADE and JET IEEE Trans. Plasma Sci. 42552 [19] BrezinsekS. etal 2015 Plasma-surface interaction in the Be/W environment: conclusions drawn from the JET-ILW for ITER J. Nucl. Mater. 46311 [20] LoarerT. etal 2013 Comparison of long term fuel retention in JET between carbon and the ITER-like wall J. Nucl. Mater. 438S108 [21] HeinolaK. etal 2015 Fuel retention in JET ITER-like wall from post-mortem analysis J. Nucl. Mater. 463961 [22] WiddowsonA.M. etal 2014 Material migration patterns and overview of first surface analysis of the JET ITER-like wall Phys. Scr. T159014010 [23] HeinolaK. etal 2016 Long-term fuel retention in JET ITER- like wall Phys. Scr. T167014075 [24] RubelM. etal 2016 An overview of fuel inventory and deposition in castellated beryllium structures in JET Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/P6-1 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) [25] WiddowsonA.M. etal 2016 Overview of fuel inventory in JET with the ITER-like wall Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) MPT/1–3 (https:// nucleus.iaea.org/sites/fusionportal/Pages/Fusion%20 Energy%20Conference.aspx) [26] SchmidK. etal 2015 WALLDYN simulations of global impurity migration in JET and extrapolations to ITER Nucl. Fusion 55053015 [27] KriegerK. etal 2013 Beryllium migration and evolution of first wall surface composition in the JET ILW configuration J. Nucl. Mater. 438262–6 [28] TaylorN., AlejaldreC. and CortesP. 2013 Progress in the Safety and Licensing of ITER Fusion Sci. Technol. 64111 [29] De TemmermanG. etal 2016 Efficiency of thermal outgassing for tritium retention measurement and removal in ITER Nucl. Mater. Energy accepted [30] HeinolaK. etal 2016 Long-term fuel retention and release in JET ITER-Like Wall at ITER-relevant baking temperatures Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/P6-2 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 37 [31] LikonenJ. etal 2016 Deuterium trapping and release in ITER-Like co-deposited layers Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome,Italy, 2016) (http://www.psi2016.enea.it/) [32] HakolaA. etal 2015 Feasibility of arc-discharge and plasma-sputtering methods in cleaning plasma-facing and diagnostics components of fusion reactors Fusion Eng. Des. 96–7101 [33] WautersT. etal 2015 Isotope exchange experiments on ITER- like wall in JET Proc. the 42nd EPS Conf. on Plasma Physics (Lisbon, Portugal, June 2015) vol 39E (ECA) P2.118 (http:// ocs.ciemat.es/EPS2015PAP/html/) [34] DouaiD. etal 2011 Recent results on ion cyclotron wall conditioning in mid and large size tokamaks J. Nucl. Mater. 415S1021 [35] LyssoivanA. etal 2012 Simulation of ITER full-field ICWC scenario in JET: RF physics aspects Plasma Phys. Control. Fusion 54074014 [36] RubelM. etal 2016 The role and application of ion beam analysis for studies of plasma-facing components in controlled fusion devices Nucl. Instrum. Methods B3714 [37] MatveevD. 2012 Computer simulations of material deposition and fuel retention in remote areas and castellated structures of fusion machines PhD Thesis Ghent University [38] BorodinD. etal 2011 ERO code benchmarking of ITER first wall beryllium erosion/re-deposition against LIM predictions Phys. Scr. T145014008 [39] BorodinD. etal 2014 Determination of Be sputtering yields from spectroscopic observations at the JET ITER-like wall based on three-dimensional ERO modelling Phys. Scr. T159014057 [40] BorodinD. etal 2016 ERO modelling of Be erosion in JET and extrapolation of the data for ITER Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/P6-3 (https:// nucleus.iaea.org/sites/fusionportal/Pages/Fusion%20 Energy%20Conference.aspx) [41] Den HarderN., BrezinsekS., PütterichT., FedorczakN., MatthewsG.F., MeigsA., StampM.F., van de SandenM.C.M., Van RooijG.J. and JET Contributors 2016 ELM-resolved divertor erosion in the JET ITER-like wall Nucl. Fusion 56026014 [42] GuillemautC. etal 2015 Ion target impact energy during Type I edge localized modes in JET ITER-like wall Plasma Phys. Control. Fusion 57085006 [43] GuillemautC. etal 2016 Experimental estimation of tungsten impurity sputtering due to Type I ELMs in JET-ITER-like wall using pedestal electron cyclotron emission and target Langmuir probe measurements Phys. Scr. T167014005 [44] BorodinD. etal 2106 Improved ERO modelling for spectroscopy of physically and chemically assisted eroded beryllium from the JET-ILW Nucl. Mater. Energy 9604 [45] BrezinsekS. etal 2015 Beryllium migration in JET ITER-like wall plasmas Nucl. Fusion 55063021 [46] BorodinD. etal 2013 Spectroscopic measurements of Be erosion at JET ILW and interpretation with ERO modelling J. Nucl. Mater. 438S267–71 [47] BorodkinaI. etal 2016 An analytical expression for the electric field and particle tracing in modelling of be erosion experiments at the JET ITER-like wall Contrib. Plasma Phys. 56640 [48] KlepperC.C. etal 2016 Estimates of RF-induced erosion at antenna-connected beryllium plasma-facing components in JET Phys. Scr. T167014035 [49] BorodkinaI. etal 2016 Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome,Italy, 2016) (submitted to Nucl. Mater. Energy) [50] SafiE. etal 2015 Atomistic simulations of the effect of reactor-relevant parameters on be sputtering J. Nucl. Mater. 463805 [51] EichTh. etal. 2016 ELM divertor heat load scaling to ITER with data from JET, MAST and ASDEX Upgrade Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (http://www. psi2016.enea.it/) [52] SieglinB. etal 2016 Assessment of divertor heat load with and without external magnetic perturbation Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/7- 3Ra (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [53] GunnJ. etal 2016 Ion orbit modelling of surface heat loads on ITER divertor vertical targets Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (Nucl. Mater. Energy) (http://www. psi2016.enea.it/) [54] PamelaS. etal 2016 Non-linear MHD simulations of ELMs in JET and quantitative comparisons to experiments Plasma Phys. Control. Fusion 58014026 [55] PamelaS. etal 2016 Multi-machine modelling of ELMs and pedestal confinement: from validation to prediction Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) TH/8-2 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) [56] FutataniS. etal 2016 Non-linear MHD simulations of pellet triggered ELMs Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto,Japan, 2016) TH/P1-25 (https://nucleus.iaea.org/ sites/fusionportal/Pages/Fusion%20Energy%20Conference. aspx) [57] Carpentier-ChouchanaS. etal 2014 Status of the ITER fulltungsten divertor shaping and heat load distribution analysis Phys. Scr. T159014002 [58] CoenenJ.W. etal 2015 ELM-induced transient tungsten melting in the JET divertor Nucl. Fusion 55023010 [59] ArnouxG. etal 2015 Thermal analysis of an unexposed tungsten edge in the JET divertor J. Nucl. Mater. 463415–9 [60] MatthewsG.F. etal 2016 Melt damage to the JET ITER-like wall and divertor Phys. Scr. T167014070 [61] CorreY. etal 2016 Heat load calculation on protruding surfaces of the JET divertor: extensive investigation of the transient W-melting Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto,Japan, 2016) EX/P6-5 (https://nucleus. iaea.org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [62] DejarnacR. etal 2016 Power loads to misaligned edges in COMPASS Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (http://www.psi2016.enea.it/) [63] KriegerK. etal 2016 Influence of inhomogeneous power flux distribution at tungsten divertor target plates on power handling capabilities Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome,Italy, 2016) (http://www.psi2016.enea.it/) [64] IglesiasD. etal 2016 Virtual prototyping tools for the JET divertor Proc. 29th Symp. on Fusion Technology (SOFT 2016) (Prague, Czech Republic, 5 September 2016) [65] PittsR.A. etal 2016 Physics conclusions in support of ITER W divertor monoblock shaping Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (http://www.psi2016.enea.it/) [66] De TemmermanG. etal 2015 Dust in ITER: creation rates, diagnosis and analysis Proc. PFMC-15, I-13 (Aix-en-Provence, France, May 2015) [67] ShimadaM. etal 2013 In-vessel dust and tritium control strategy in ITER J. Nucl. Mater. 438S996 [68] Baron-WiechecA. etal 2015 First dust study in JET with the ITER-like wall: sampling, analysis and classification Nucl.Fusion 55113033 Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 38 [69] Fortuna-ZalesnaE. etal 2016 Detailed survey of dust particles from JET with the ITER like wall: origin, composition and internal structure Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto,Japan, 2016) EX/P6-20 [70] ToliasP. etal 2016 Dust remobilization in fusion plasmas under steady state conditions Plasma Phys. Control. Fusion 58025009 [71] RatynskaiaS. etal 2016 Interaction of adhered metallic dust with transient plasma heat loads Nucl. Fusion 56066010 [72] FlanaganJ.C. etal 2015 Characterising dust in JET with the new ITER-like wall Plasma Phys. Control. Fusion 57014037 [73] AshikawaN. etal 2016 Comprehensive analysis of metal dust particles in JET-ILW, and impact on fusion reactor Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/ P6-19 (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [74] RatynskaiaS. etal 2013 Migration of tungsten dust in tokamaks: role of dust-wall collisions Nucl. Fusion 53123002 [75] VignitchoukL. etal 2014 Dust-wall and dust-plasma interaction in the MIGRAINe code Plasma Phys. Control. Fusion 56095005 [76] SertoliM. etal 2015 Impact of W events and dust on JET-ILW operation J. Nucl. Mater. 463837 [77] IvanovaD. etal 2014 An overview of overview of the comprehensive first mirrors test in JET with ITER-like wall Phys. Scr. T159014011 [78] Garcia-CarrascoA. etal 2016 Modification of diagnostic mirrors in JET Nucl. Mater. Energy submitted [79] Fortuna-ZalesnaE. etal Dust studies following the second campaign of JET with ITER-like wall Nucl. Mater. Energy submitted 2016 [80] PittsR.A. etal 2009 Status and physics basis of the ITER divertor Phys. Scr. T138014001 [81] LuoX. etal 2011 Experimental results and numerical modeling of a high-performance large-scale cryopump J.Vac. Sci. Technol. A29041601 [82] BirdG.A. 1994 Molecular Gas Dynamics and the Direct Simulation of Gas Flows (New York: Oxford Science Publications) [83] VaroutisC., Gleason-GonzálezS., MoultonD., KrueziU., GrothM., DayChr., WiesenS., HartingD. and JET EFDA Contributors 2014 Simulation of neutral gas flow in the JET sub-divertor and comparison with experimental results Paper Presented at 25th IAEA Fusion Energy Conf. (StPetersburg, Russia, 2014) FIP/P8-8 (http://www-naweb.iaea.org/napc/ physics/FEC/FEC2014/fec_sourcebook_online.pdf) [84] Gleason-GonzálezC. etal 2103 Simulation of neutral gas flow in a tokamak divertor using the Direct Simulation Monte Carlo method Fusion Eng. Des. 891042–7 [85] Gleason-GonzálezC. etal 2016 Simulation of collisional effects on divertor pumping in JT-60SA Fusion Eng. Des. [86] DayChr. etal 2016 Effect of the dome on the collisional neutral gas flow in the DEMO divertor IEEE Trans. PlasmaSci. [87] LehnenM. etal 2015 Disruptions in ITER and strategies for their control and mitigation J. Nucl. Mater. 46339–48 [88] JachmichS. etal 2016 Disruption mitigation experiments at JET in support of ITER Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome,Italy, 2016) (to be published J. Nucl. Mater. Energy) [89] JachmichS. etal Disruption mitigation at JET using massive gas injection Proc. 43rd European Physical Society Conf. on Plasma Physics (EPS) (Leuven, Belgium, 2016) vol 40A ECA (http://ocs.ciemat.es/EPS2016PAP/html/) [90] JoffrinE. etal 2016 Disruption studies in the JET metallic wall Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/9-1 (https://nucleus.iaea.org/sites/ fusionportal/Pages/Fusion%20Energy%20Conference.aspx) [91] LehnenM. etal 2013 Impact and mitigation of disruptions with the ITER-like wall in JET Nucl. Fusion 53093007 [92] ReuxC. etal 2015 Run-away electron beam generation and mitigation during disruptions at JET-ILW Nucl. Fusion 55093013 [93] LehnenM. etal 2015 Radiation asymmetries during the thermal quench of massive gas injection disruptions in JET Nucl. Fusion 55123027 [94] FilA. etal 2015 Three-dimensional non-linear magnetohydrodynamic modeling of massive gas injection triggered disruptions in JET Phys. Plasmas 22062509 [95] NardonE., FilA., HoelzlM., HuijsmansG. and JET Contributors 2017 Progress in understanding disruptions triggered by massive gas injection via 3D non-linear MHD modelling with JOREK Plasma Phys. Control. Fusion 59014006 [96] NardonE., FilA., ChauveauP., TamainP., GuirletR., KoslowskiH.R., LehnenM., ReuxC., Saint-LaurentF. and JET Contributors 2017 On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection Nucl. Fusion 57016027 [97] de VriesP.C. etal 2016 Scaling of the MHD perturbation amplitude required to trigger a disruption and predictions for ITER Nucl. Fusion 56026007 [98] RattáG.A., VegaJ., MurariA., VagliasindiG., JohnsonM.F., de VriesP.C. and JET-EFDA Contributors 2010 An advanced disruption predictor for JET tested in a simulated real time environment Nucl. Fusion 50025005 [99] LópezJ.M., VegaJ., AlvesD., Dormido-CantoS., MurariA., RamírezJ.M., FeltonR., RuizM., de ArcasG. and JETEFDA Contributors 2014 Implementation of the disruption predictor APODIS in JET’s real-time network using the MARTe framework IEEE Trans. Nucl. Sci. 61741–4 [100] VegaJ., Dormido-CantoS., LópezJ.M., MurariA., RamírezJ.M., MorenoR., RuizM., AlvesD., FeltonR. and JET-EFDA Contributors 2013 Results of the JET real-time disruption predictor in the ITER-like wall campaigns Fusion Eng. Des. 881228 [101] Dormido-CantoS., VegaJ., RamírezJ.M., MurariA., MorenoR., LópezJ.M., PereiraA. and JET-EFDA Contributors 2013 Development of an efficient real-time disruption predictor from scratch on JET and implications for ITER Nucl. Fusion 53113001 [102] VegaJ., MurariA., Dormido-CantoS., MorenoR., PereiraA., AceroA. and JET-EFDA Contributors 2014 Adaptive high learning rate probabilistic disruption predictors from scratch for the next generation of tokamaks Nucl. Fusion 54123001 [103] PereiraA., VegaJ., MorenoR., Dormido-CantoS., RattáG.A., PavónF. and JET-EFDA Contributors 2015 Feature selection for disruption prediction from scratch in JET by using genetic algorithms and probabilistic predictors Fusion Eng. Des. 96–7907 [104] MorenoR., VegaJ., Dormido-CantoS., PereiraA., MurariA. and JET Contributors 2016 Fusion Sci. Technol. 69485 [105] VegaJ., MurariA., Dormido-CantoS., MorenoR., PereiraA., RattáG.A. and JET Contributors 2015 Disruption precursor detection: combining the time and frequency domains 26th Symp. on Fusion Engineering (SOFE 2015) (Austin, 31 May 31–4 June 2015) (https://www.ieee.org/conferences_ events/conferences/conferencedetails/index. html?Conf_ID=33899) [106] VegaJ., MorenoR., PereiraA., Dormido-CantoS., MurariA. and JET Contributors 2015 Advanced disruption predictor based on the locked mode signal: application to JET 1st EPS Conf. on Plasma Diagnostics (Villa Mondragone, Frascati, Italy, 14–17 April 2015) (https://pos.sissa.it/archive/conferences/240/028/ ECPD2015_028.pdf) Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 39 [107] EsquembriS., VegaJ., MurariA., RuizM., BarreraE., Dormido-CantoS., FeltonR., TsalasM., ValcarcelD. and JET Contributors 2016 Real-time implementation in JET of the SPAD disruption predictor using MARTe 20th IEEE Real-Time Conf. (Padua, Italy, 5–10 June 2016) (https:// indico.cern.ch/event/390748/contributions/1825167/ attachments/1281638/1904245/CR_RTA2_30v2.pdf) [108] MurariA., PelusoE., VegaJ., GelfusaM., LungaroniM. and GaudioP. 2017 Determining the prediction limits of models and classifiers using an information theoretical indicator Nucl. Fusion 57016024 [109] CannasB. etal 2013 Automatic disruption classification based on manifold learning for real-time applications on JET Nucl. Fusion 53093023 [110] MurariA. etal 2008 Prototype of an adaptive disruption predictor for JET based on fuzzy logic and regression trees Nucl. Fusion 48035010 [111] MurariA., BoutotP., VegaJ., GelfusaM., MorenoR., VerdoolaegeG., de VriesP.C. and JET-EFDA Contributors 2013 Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions Nucl. Fusion 53033006 [112] MartinY.R. etal 2008 Power requirement for accessing the H-mode in ITER J. Phys.: Conf. Ser. 123012033 [113] RyterF. etal 2013 Survey of the H-mode power threshold and transition physics studies in ASDEX Upgrade Nucl.Fusion 53113003 [114] MaggiC.F. etal 2014 L–H power threshold studies in JET with Be/W and C wall Nucl. Fusion 54023007 [115] BourdelleC. etal 2014 L to H mode transition: on the role of Zeff Nucl. Fusion 54022001 [116] MaggiC.F. etal 2014 Role of low-Z impurities in L–H transitions in JET Proc. 41st EPS Conf. on Plasma Physics (Berlin, 2014) ECA vol 38F P1.004 (http://ocs.ciemat.es/ EPS2014PAP/html/) [117] DelabieE. etal 2015 The relation between divertor conditions and the L–H threshold on JET-ILW Proc. the 42nd EPS Conf. (Lisbon, 2015) (http://ocs.ciemat.es/ EPS2015PAP/html/) [118] ChankinA.V. etal 2016 Possible influence of near SOL plasma on the H-mode power threshold Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (http://www.psi2016. enea.it/) [119] DelabieE. etal 2015 L–H threshold experiments in hydrogen plasmas in JET-ILW Proc. 57th Annual Meeting of the APS Division of Plasma Physics (Savannah,GA, 2015) (http://meetings.aps.org/Meeting/ DPP15/Content/3000) [120] HillesheimJ.C. etal 2016 Role of stationary zonal flows and momentum transport for L–H transitions in JET Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/5-2 (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [121] HillesheimJ.C. etal 2016 Stationary zonal flows during the formation of the edge transport barrier in the JET Tokamak Phys. Rev. Lett. 116065002 [122] SolanoE.R. etal 2017 MHD observations around L–H transitions in JET Nucl. Fusion 57022021 [123] BirkenmeierG. etal 2016 Magnetic structure and frequency scaling of limit-cycle oscillations close to L- to H-mode transitions Nucl. Fusion 56086009 [124] AngioniC. etal 2014 Tungsten transport in JET H-mode plasmas in hybrid scenario, experimental observations and modelling Nucl. Fusion 54083028 [125] CassonF.J. etal 2015 Theoretical description of heavy impurity transport and its application to the modelling of tungsten in JET and ASDEX upgrade Plasma Phys. Control. Fusion 57014031 [126] AngioniC. etal 2016 Progress in the theoretical description and the experimental characterization of tungsten transport in tokamaks Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) TH/P2-6 (https://nucleus.iaea. org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [127] ValisaM. etal 2016 The role of ELM’s and inter-ELM phases in the transport of heavy impurities JET Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/ P6-17 (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [128] LoarteA. etal 2015 Tungsten impurity transport experiments in Alcator C-Mod to address high priority research and development for ITER Phys. Plasmas 22056117 [129] GonicheM. etal 2016 Ion cyclotron resonance heating for tungsten control in various JET H-mode scenarios Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/P6-16 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) [130] de VriesP.C. etal 2016 Multi-machine analysis of termination scenarios, providing the specifications for controlled shutdown of ITER discharges Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/ P6-41 (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [131] KoechlF. etal 2016 Evolution and control of tungsten transport in the termination phase of JET H-mode discharges and implications for ITER Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/ P6-15 (https://nucleus.iaea.org/sites/fusionportal/Pages/ Fusion%20Energy%20Conference.aspx) [132] RomanelliM. etal 2014 JINTRAC: a system of codes for integrated simulation of Tokamak scenarios Plasma Fusion Res. 93403023 [133] LoarteA. etal 2016 Evaluation of tungsten transport and concentration control in ITER scenarios Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) (https:// nucleus.iaea.org/sites/fusionportal/Pages/Fusion%20 Energy%20Conference.aspx) [134] HuberA. etal 2016 Comparative H-mode density limit studies in JET and AUG Proc. 22nd Int. Conf. on Plasma Surface Interactions in Controlled Fusion Devices (Rome, Italy, 2016) (submitted in Nucl. Mater. Energy) [135] HuberA. etal 2016 The effect of the isotope on the H-mode density limit Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/ PDP-8 (https://nucleus.iaea. org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [136] GoldstonR.J. 2015 Theoretical aspects and practical implications of the heuristic drift SOL model J.Nucl.Mater. 463397 [137] GoldstonR.J. 2012 Heuristic drift-based model of the power scrape-off width in low-gas-puff H-mode tokamaks Nucl. Fusion 52013009 [138] BeurskensM. etal 2014 Global and pedestal confinement in JET with a Be/W metallic wall Nucl. Fusion 54043001 [139] KimH.T. etal 2015 Comparative analysis of core heat transport of JET high density H-mode plasmas in carbon wall and ITER-like wall Plasma Phys. Control. Fusion 57065002 [140] GiroudC. etal 2013 Impact of nitrogen seeding on confinement and power load control of a high-triangularity JET ELMy H-mode plasma with a metal wall Nucl. Fusion 53113025 [141] FrassinettiL. etal 2017 Dimensionless scans in low δ baseline JET-ILW plasmas and comparison with JET-C Plasma Phys. Control. Fusion 59014014 [142] FrassinettiL. etal 2017 Global and pedestal confinement and pedestal structure in dimensionless collisionality Nucl. Fusion 57 (2017) 102001 X. Litaudon etal 40 scans of low triangularity H-mode plasmas in JET-ILW Nucl.Fusion 57016012 [143] LuceT.C. etal 2008 Application of dimensionless parameter scaling techniques to the design and interpretation of magnetic fusion experiments Plasma Phys. Control. Fusion 50043001 [144] ManticaP. etal 2011 A key to improved ion core confinement in the JET tokamak: ion stiffness mitigation due to combined plasma rotation and low magnetic shear Phys. Rev. Lett. 107135004 [145] CitrinJ. etal 2013 Nonlinear stabilization of tokamak microturbulence by fast ions Phys. Rev. Lett. 111155001 [146] BonanomiN., CitrinJ., ManticaP. and JET Contributors 2015 Impact of electron scale modes on electron heat transport in the JET tokamak Proc. 42nd EPS Conf. on Plasma Physics (Lisbon, 2015) ECA vol 39E P2.122 (http://ocs.ciemat.es/EPS2015PAP/html/) [147] BonanomiN. etal 2016 Electron heat transport in JET from ion to electron scales: experimental investigation and gyrokinetic simulations Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto,Japan, 2016) EX/P6-14 (https://nucleus. iaea.org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [148] JenkoF., DorlandW., KotschenreutherM. and RogersB.N. 2000 Electron temperature gradient driven turbulence Phys.Plasmas 71904 [149] CandyJ. and WaltzR.E. 2003 An Eulerian gyrokinetic- Maxwell solver J. Comput. Phys. 186545 [150] GörlerT. and JenkoF. 2008 Scale separation between electron and ion thermal transport Phys. Rev. Lett. 100185002 [151] HowardN.T. etal 2014 Investigation of the transport shortfall in Alcator C-Mod L-mode plasmas Phys. Plasmas 21032510 [152] MaeyamaS. etal 2015 Cross-scale interactions between electron and ion scale turbulence in a tokamak plasma Phys.Rev. Lett. 114255002 [153] MaggiC.F. etal 2015 Pedestal confinement and stability in JET-ILW ELMy H-modes Nucl. Fusion 55113031 [154] LeylandM.J. etal 2015 The H-mode pedestal structure and its role on confinement in JET with a carbon and metal wall Nucl. Fusion 55013019 [155] MaggiC.F. etal 2016 Studies of the pedestal structure in JET with the ITER-like wall Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/3-3 (https:// nucleus.iaea.org/sites/fusionportal/Pages/Fusion%20 Energy%20Conference.aspx) [156] UranoH. etal 2016 Global stabilization effect of Shafranov shift on the edge pedestal plasmas in JET and JT-60U Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/3-4 (https://nucleus.iaea.org/sites/fusionportal/ Pages/Fusion%20Energy%20Conference.aspx) [157] AibaN. etal 2016 Diamagnetic MHD equationsfor plasmas with fast flow and its application to ELM analysis in JT-60U and JET-ILW Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) TH/8-1 (https://nucleus. iaea.org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [158] ChapmanI.T. etal 2016 Joint EU experiments tailoring the plasma evolution to maximise the pedestal performance ahead of JET D–T and ITER Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/3-6 (https:// nucleus.iaea.org/sites/fusionportal/Pages/Fusion%20 Energy%20Conference.aspx) [159] StefanikovaE. etal 2016 Effect of the relative shift between the electron density and temperature pedestal position on the pedestal stability in JET-ILW Proc. 43rd European Physical Society Conf. on Plasma Physics (EPS) (Leuven,Belgium 2016) ECA vol 40A O4.117 (http://ocs. ciemat.es/EPS2016PAP/html/) [160] SaarelmaS. etal 2015 The effects of impurities and core pressure on pedestal stability in Joint European Torus (JET) Phys. Plasmas 22056115 [161] DunneM. etal 2017 The role of the density profile in the ASDEX-Upgrade pedestal structure Plasma Phys. Control. Fusion 59014017 [162] BeurskensM.N.A. etal 2011 H-mode pedestal scaling in DIII-D, ASDEX Upgrade, and JET Phys. Plasmas 18056120 [163] OsborneT.H. etal 2015 Enhanced H-mode pedestals with lithium injection in DIII-D Nucl. Fusion 55063018 [164] WilsonH.R., SnyderP.B., HuysmansG.T.A. and MillerR.L. 2002 Numerical studies of edge localized instabilities in tokamaks Phys. Plasmas 91277 [165] SnyderP.B. etal 2002 Edge localized modes and the pedestal: a model based on coupled peeling–ballooning modes Phys. Plasmas 92037 [166] ParailV. etal 2015 Coupled core-SOL modelling of W contamination in H-mode JET plasmas with ITER-like wall J. Nucl. Mater. 463611 [167] ChallisC. etal 2015 Improved confinement in JET high β plasmas with an ITER-like wall Nucl. Fusion 55053031 [168] GarciaJ. etal 2015 Key impact of finite-beta and fast ions in core and edge tokamak regions for the transition to advanced scenarios Nucl. Fusion 55053007 [169] ArtaudF. etal 2010 The CRONOS suite of codes for integrated tokamak modelling Nucl. Fusion 50043001 [170] GarciaJ. etal 2014 Physics comparison and modelling of the JET and JT-60U core and edge: towards JT-60SA predictions Nucl. Fusion 54093010 [171] CordeyJ.G. etal 2003 A two-term model of the confinement in Elmy H-modes using the global confinement and pedestal databases Nucl. Fusion 43670 [172] SaarelmaS. etal 2016 private communication [173] SnyderP.B., GroebnerR.J., LeonardA.W., OsborneT.H. and WilsonH.R. 2009 Development and validation of a predictive model for the pedestal height Phys. Plasmas 16056118 [174] SnyderP.B. etal 2011 A first-principles predictive model of the pedestal height and width: development, testing and ITER optimization with the EPED model Nucl. Fusion 51103016 [175] GarciaJ. etal 2017 Challenges in the extrapolation from D–D to D–T plasmas: analysis and theory based predictions Plasma Phys. Control. Fusion 59014023 [176] WeisenH. etal 2005 Collisionality and shear dependences of density peaking in JET and extrapolation to ITER Nucl.Fusion 45L1 [177] WeisenH. etal 2006 Scaling of density peaking in JET H-modes and implications for ITER Plasma Phys. Control. Fusion 48A457 [178] AngioniC. etal 2007 Scaling of density peaking in H-mode plasmas based on a combined database of AUG and JET observations Nucl. Fusion 471326 [179] ValovicM. etal. 2004 Density peaking in low collisionality ELMy H-mode in JET Phys. Control. Fusion 461877 [180] GarzottiL. etal. 2006 Simulations of source and anomalous pinch effects on the density profile peaking of JET H-mode plasmas Nucl. Fusion 46994 [181] ValovicM. etal 2007 On the correlation between density profile and particle flux in H-mode tokamak plasmas and the implication for ITER Nucl. Fusion 47196 [182] TalaT.J.J. etal 2016 Density peaking in JET—driven by fuelling or transport? Preprint: 2016 IAEA Fusion Energy Conf. (Kyoto, Japan, 2016) EX/P6-12 (https://nucleus. iaea.org/sites/fusionportal/Pages/Fusion%20Energy%20 Conference.aspx) [183] SalmiA. etal 2015 Dimensionless Collisionality Scans for Core Particle Transport in JET 42nd EPS Conf. (Lisbon, Portugal, 22–26 June 2015) ECA vol 39E P2.136 (http://ocs.ciemat.es/EPS2015PAP/html/) Nucl. Fusion 57 (2017) 102001